Duke University
Private University • US
Showing 198 courses from Duke
Java Programming and Software Engineering Fundamentals - Duke
Duke University (via Coursera)
Java Programming and Software Engineering Fundamentals - Duke is a comprehensive beginner-level resource offered by Duke University, focused on building practical skills in programming and data structures. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in programming and data structures, including algorithms, data structures, system design, and coding interview patterns. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Master Java syntax, OOP principles, and the JVM Work with collections, generics, and streams Handle exceptions, files, and multithreading Build console and desktop apps using core Java Duration: Estimated duration: 80 hours of content, designed to be completed in 8-16 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into programming and data structures Freelancers wanting to add new services to their portfolio Self-learners passionate about programming and data structures and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as Software Development Engineer (SDE), Software Engineer, Backend Developer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 6-12 LPA Mid-level / 2-5 years: Rs 15-30 LPA Senior / 5+ years: Rs 30-60 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Google, Amazon, Microsoft, Flipkart, PhonePe, Atlassian. Strong programming and DSA skills are the 1 factor in clearing technical interviews at product companies. Companies like Google, Amazon, Microsoft, Flipkart, and PhonePe all use coding rounds as their primary hiring filter. The Indian tech interview landscape typically involves 2-3 DSA rounds, 1 system design round (for experienced roles), and 1-2 behavioral rounds. Candidates who have solved 200+ quality problems on platforms like LeetCode consistently report higher interview success rates. Duke University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Java Programming and Software Engineering Fundamentals - Duke
Duke University (via Coursera)
Java Programming and Software Engineering Fundamentals - Duke is a comprehensive beginner-level resource offered by Duke University, focused on building practical skills in programming and data structures. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in programming and data structures, including algorithms, data structures, system design, and coding interview patterns. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Master Java syntax, OOP principles, and the JVM Work with collections, generics, and streams Handle exceptions, files, and multithreading Build console and desktop apps using core Java Duration: Estimated duration: 100 hours of content, designed to be completed in 10-20 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into programming and data structures Freelancers wanting to add new services to their portfolio Self-learners passionate about programming and data structures and wanting structured guidance Pricing: The course content is free to access. A verified certificate is available for a fee. Completing this resource and building related skills can prepare you for roles such as Software Development Engineer (SDE), Software Engineer, Backend Developer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 6-12 LPA Mid-level / 2-5 years: Rs 15-30 LPA Senior / 5+ years: Rs 30-60 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include Google, Amazon, Microsoft, Flipkart, PhonePe, Atlassian. Strong programming and DSA skills are the 1 factor in clearing technical interviews at product companies. Companies like Google, Amazon, Microsoft, Flipkart, and PhonePe all use coding rounds as their primary hiring filter. The Indian tech interview landscape typically involves 2-3 DSA rounds, 1 system design round (for experienced roles), and 1-2 behavioral rounds. Candidates who have solved 200+ quality problems on platforms like LeetCode consistently report higher interview success rates. Duke University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Introduction to Public Speaking - Duke University
Duke University (via Coursera)
Introduction to Public Speaking - Duke University is a comprehensive beginner-level resource offered by Duke University, focused on building practical skills in English and communication. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in English and communication, including spoken English, grammar, business writing, presentation skills, and interview preparation. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 12 hours of content, designed to be completed in 2-3 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into English and communication Freelancers wanting to add new services to their portfolio Self-learners passionate about English and communication and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as any professional role requiring strong communication. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: 20-30% salary premium over peers Mid-level / 2-5 years: 30-40% salary premium, faster promotions Senior / 5+ years: Leadership roles, client-facing positions Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include all MNCs, BPOs, IT companies, consulting firms. Communication skills are consistently rated as the 1 soft skill by Indian employers. Studies show that professionals with strong English communication earn 20-40% more than peers with similar technical abilities. In client-facing roles, consulting, and management positions, communication skills are often the differentiator for promotion. With India's growing integration into the global economy, English proficiency opens doors to international remote work opportunities. Duke University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Excel to MySQL: Analytic Techniques for Business - Duke
Duke University (via Coursera)
Excel to MySQL: Analytic Techniques for Business - Duke is a comprehensive beginner-level resource offered by Duke University, focused on building practical skills in data science and analytics. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in data science and analytics, including Python, SQL, Pandas, NumPy, data visualization, statistics, and machine learning basics. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Write SQL queries to retrieve, filter, and aggregate data Master JOINs, subqueries, and window functions Design normalized database schemas Optimize query performance with indexes and execution plans Duration: Estimated duration: 100 hours of content, designed to be completed in 10-20 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into data science and analytics Freelancers wanting to add new services to their portfolio Self-learners passionate about data science and analytics and wanting structured guidance Pricing: The course content is free to access. A verified certificate is available for a fee. Completing this resource and building related skills can prepare you for roles such as Data Analyst, Business Analyst, Data Scientist, Analytics Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 4-8 LPA Mid-level / 2-5 years: Rs 10-22 LPA Senior / 5+ years: Rs 25-50 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include TCS, Infosys, Flipkart, Amazon, Swiggy, Zomato, PhonePe. The data science industry in India is projected to grow at 27% CAGR through 2028. Companies across all sectors — from banking (HDFC, ICICI) to e-commerce (Flipkart, Amazon) to healthcare (Practo, PharmEasy) — are building data teams. India currently has a shortage of 200,000+ data professionals, making this one of the best fields to enter right now. Cities like Bangalore, Hyderabad, Pune, and Gurgaon have the highest concentration of data science jobs. Duke University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Data Science Math Skills - Duke University
Duke University (via Coursera)
Data Science Math Skills - Duke University is a comprehensive beginner-level resource offered by Duke University, focused on building practical skills in data science and analytics. Whether you're a complete beginner looking to start a new career or a professional aiming to upgrade your skills, this resource provides a thorough learning experience. This is a structured online course with a carefully designed curriculum. Each module builds on the previous one, creating a logical progression from fundamentals to advanced topics. The course typically includes video lectures, reading materials, hands-on exercises, quizzes, and sometimes peer-reviewed assignments. This structured approach ensures you don't miss any critical concepts and build a solid foundation. This resource covers topics essential for success in data science and analytics, including Python, SQL, Pandas, NumPy, data visualization, statistics, and machine learning basics. The curriculum is structured to build your knowledge progressively — starting with foundational concepts and advancing to real-world applications. By the end, you should be able to: Understand the core concepts and theoretical foundations Apply your knowledge through hands-on exercises and small projects Build the practical skills employers actually screen for Develop the problem-solving approach used by working professionals Duration: Estimated duration: 15 hours of content, designed to be completed in 2-3 weeks at a comfortable pace. No prior experience is required. This course starts from the absolute basics and gradually builds up complexity. A computer with internet access is all you need to get started. This resource is designed for a wide audience: Students (B.Tech, BCA, MCA, BSc) looking to complement their academic learning with practical, industry-relevant skills Fresh graduates preparing for campus placements or off-campus interviews Working professionals looking to upskill, switch domains, or advance their careers Career changers transitioning from non-tech backgrounds into data science and analytics Freelancers wanting to add new services to their portfolio Self-learners passionate about data science and analytics and wanting structured guidance Pricing: This resource is completely free with no hidden charges. Completing this resource and building related skills can prepare you for roles such as Data Analyst, Business Analyst, Data Scientist, Analytics Engineer. Realistic salary bands in India (2025-2026), based on Naukri/AmbitionBox data: Freshers / 0-2 years: Rs 4-8 LPA Mid-level / 2-5 years: Rs 10-22 LPA Senior / 5+ years: Rs 25-50 LPA Actual offers vary heavily by city, company tier, and how strong your portfolio or interview performance is. Companies actively hiring in this space include TCS, Infosys, Flipkart, Amazon, Swiggy, Zomato, PhonePe. The data science industry in India is projected to grow at 27% CAGR through 2028. Companies across all sectors — from banking (HDFC, ICICI) to e-commerce (Flipkart, Amazon) to healthcare (Practo, PharmEasy) — are building data teams. India currently has a shortage of 200,000+ data professionals, making this one of the best fields to enter right now. Cities like Bangalore, Hyderabad, Pune, and Gurgaon have the highest concentration of data science jobs. Duke University is a well-established platform trusted by millions of learners worldwide. This particular resource has been selected by our editorial team based on: Content quality — comprehensive coverage with clear explanations Practical focus — emphasis on hands-on skills over pure theory Student outcomes — positive reviews and career success stories Indian relevance — content applicable to the Indian job market and interview patterns Updated curriculum — material reflects current industry practices and tools We regularly review and update our recommendations to ensure they remain relevant and high-quality.
Developing Explainable AI (XAI)
Duke University (via Coursera)
As Artificial Intelligence (AI) becomes integrated into high-risk domains like healthcare, finance, and criminal justice, it is critical that those responsible for building these systems think outside the black box and develop systems that are not only accurate, but also transparent and trustworthy. This course provides a comprehensive introduction to Explainable AI (XAI), empowering you to develop AI solutions that are aligned with responsible AI principles. Through discussions, case studies, and real-world examples, you will gain the following skills: 1. Define key XAI terminology and concepts, including interpretability, explainability, and transparency. 2. Evaluate different interpretable and explainable approaches, understanding their trade-offs and applications. 3. Integrate XAI explanations into decision-making processes for enhanced transparency and trust. 4. Assess XAI systems for robustness, privacy, and ethical considerations, ensuring responsible AI development. 5. Apply XAI techniques to cutting-edge areas like Generative AI, staying ahead of emerging trends. This course is ideal for AI professionals, data scientists, machine learning engineers, product managers, and anyone involved in developing or deploying AI systems. By mastering XAI, you'll be equipped to create AI solutions that are not only powerful but also interpretable, ethical, and trustworthy, solving critical challenges in domains like healthcare, finance, and criminal justice. To succeed in this course, you should have experience building AI products and a basic understanding of machine learning concepts like supervised learning and neural networks. The course will cover explainable AI techniques and applications without deep technical details.
مقاييس الأعمال للشركات التي تعتمد على البيانات
Duke University (via Coursera)
في هذه الدورة التدريبية، ستتعلم أفضل الممارسات لكيفية استخدام تحليلات البيانات لتجعل أي شركة لها قدرة أكبر على التنافس والربح. سيمكنك التعرف على أهم مقاييس الأعمال وتمييزها عن البيانات العادية. وستكون لديك صورة واضحة عن الأدوار الحيوية المختلفة التي يضطلع بها كل من محللي الأعمال، ومحللي بيانات الأعمال، وعلماء البيانات في مختلف أنواع الشركات. وستعرف بالضبط أي المهارات مطلوبة للتوظيف في هذه الأعمال التي يرتفع الطلب عليها والنجاح فيها. وفي النهاية، سيمكنك الاستعانة بالقائمة المرجعية التي توفرها الدورة التدريبية؛ لتقييم أي شركة بناءً على كيفية تبنّيها لثقافة البيانات الضخمة بفعاليّة. تُحدث الشركات الرقمية مثل Amazon، وUber، وAirbnb تحوّلًا في الصناعات بالكامل من خلال استخدامها الإبداعي للبيانات الضخمة.. وستدرك لِمَ تكون هذه الشركات معرقلة للغاية، وكيفية استخدامها لتقنيات تحليل البيانات؛ لكي تتفوق في قدرتها التنافسية على الشركات التقليدية.
Business Impact
Duke University (via Coursera)
In this course, you will learn how to apply financial principles and analyses to make strategic decisions that drive business growth, enhance operational efficiency, and maximize shareholder value. You will apply these concepts by engaging in strategic decision-making exercises and completing assessments that link financial insights to business outcomes. This course is ideal for non-financial managers or professionals who seek to enhance their financial acumen to make better business decisions. No prior experience in finance is required. However, a basic understanding of business operations and strategic thinking will be beneficial.
Drones for Environmental Science
Duke University (via Coursera)
How can drones be used for good in environmental science? What types of data can scientists collect, and how should they go about collecting it using drones? Why should someone integrate drones into their existing career or pursue this field? This Duke Environment+ course serves as an introduction for anyone interested in learning more about drone use in the environmental sciences. No background knowledge in drones is assumed or necessary. Over the course of four weeks, you will discover the basics of drone use in the environmental sciences, including specific benefits of using drones for scientific research; types of drones and how they are used for different purposes and missions; and best research practices, including legal and ethical concerns. The final week of the course will help you get started on exploring different career paths that involve drones by introducing you to professionals working with this technology in the environmental sciences. By the end of the course, you should be better equipped to consider how to use drones for your own research interests, and you will be better prepared for the more in-depth Environment+ course sequence UAS Applicants and Operations in Environmental Science, should you decide to continue your studies.
Explainable Machine Learning (XAI)
Duke University (via Coursera)
As Artificial Intelligence (AI) becomes integrated into high-risk domains like healthcare, finance, and criminal justice, it is critical that those responsible for building these systems think outside the black box and develop systems that are not only accurate, but also transparent and trustworthy. This course is a comprehensive, hands-on guide to Explainable Machine Learning (XAI), empowering you to develop AI solutions that are aligned with responsible AI principles. Through discussions, case studies, programming labs, and real-world examples, you will gain the following skills: 1. Implement local explainable techniques like LIME, SHAP, and ICE plots using Python. 2. Implement global explainable techniques such as Partial Dependence Plots (PDP) and Accumulated Local Effects (ALE) plots in Python. 3. Apply example-based explanation techniques to explain machine learning models using Python. 4. Visualize and explain neural network models using SOTA techniques in Python. 5. Critically evaluate interpretable attention and saliency methods for transformer model explanations. 6. Explore emerging approaches to explainability for large language models (LLMs) and generative computer vision models. This course is ideal for data scientists or machine learning engineers who have a firm grasp of machine learning but have had little exposure to XAI concepts. By mastering XAI approaches, you'll be equipped to create AI solutions that are not only powerful but also interpretable, ethical, and trustworthy, solving critical challenges in domains like healthcare, finance, and criminal justice. To succeed in this course, you should have an intermediate understanding of machine learning concepts like supervised learning and neural networks.
Spark, Hadoop, and Snowflake for Data Engineering
Duke University (via Coursera)
e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programmingGain the skills for building efficient and scalable data pipelines. Explore essential data engineering platforms (Hadoop, Spark, and Snowflake) as well as learn how to optimize and manage them. Delve into Databricks, a powerful platform for executing data analytics and machine learning tasks, while honing your Python data science skills with PySpark. Finally, discover the key concepts of MLflow, an open-source platform for managing the end-to-end machine learning lifecycle, and learn how to integrate it with Databricks. This course is designed for learners who want to pursue or advance their career in data science or data engineering, or for software developers or engineers who want to grow their data management skill set. In addition to the technologies you will learn, you will also gain methodologies to help you hone your project management and workflow skills for data engineering, including applying Kaizen, DevOps, and Data Ops methodologies and best practices. With quizzes to test your knowledge throughout, this comprehensive course will help guide your learning journey to become a proficient data engineer, ready to tackle the challenges of today's data-driven world.
Renewable Energy and Green Building Entrepreneurship
Duke University (via Coursera)
Welcome to the course where you learn to launch a new business in the energy, finance, real estate, design, engineering, or environmental sectors, while also helping you create positive environmental and human health impacts around the world. We will integrate tools, trends, and tips from the field of entrepreneurship as a career path for making a difference and generating wealth in the renewable energy and green building sectors. This is not a course about theory. Instead, we focus on real world application, step-by-step advice, and case studies. After completing this course, students will be able to: Define key business opportunities, challenges, and potential solutions in the renewable energy and green building sectors. Analyze a successful business in renewable energy or green building. Identify 2 to 3 problems you might solve with either renewable energy or green building products or services. Plan for engaging with investors who might finance a new business. Take real world first steps towards launching a new business or corporate initiative, by applying the 1-page business idea summary template and the Business Model Canvas to generating and refining your own new business ideas.
Psalms and the Arts
Duke University (via Coursera)
The Psalms offer a path to express a range of human emotion and to encounter God in a new way. In times of great joy or deep grief, how might the Psalms help shape who we are – and who we are to one another? This course invites you to learn from experts in biblical interpretation and the arts to deepen your personal and communal engagement with the Psalms and the arts. In this course, you will meditate on psalms and artworks, engage with the Psalms theologically, explore artful interpretations of the Psalms, and examine the role of the Psalms in the life of the church. At the heart of the course and each session is a series of conversations with artists and scholars who give attention to the Psalms in their professional work and in their worship and prayer practice. This course is valuable for church leaders and members—individually or in community—who want to read and interpret scripture in conversation with the arts. You do not need to have a formal theological education to enroll in this course.
Think Again I: How to Understand Arguments
Duke University (via Coursera)
In this course, you will learn what an argument is. The definition of argument will enable you to identify when speakers are giving arguments and when they are not. Next, you will learn how to break an argument into its essential parts, how to put them in order to reveal their connections, and how to fill in gaps in an argument by adding suppressed premises. By the end of this course, you will be better able to understand and appreciate arguments that you and other people present. Suggested Readings: Students who want more detailed explanations or additional exercises or who want to explore these topics in more depth should consult Understanding Arguments: An Introduction to Informal Logic, Ninth Edition, Concise, Chapters 1-5, by Walter Sinnott-Armstrong and Robert Fogelin. Course Format: Each week will be divided into multiple video segments that can be viewed separately or in groups. There will be short ungraded quizzes after each segment (to check comprehension) and a longer graded quiz at the end of the course.
Decentralized Finance (DeFi) Primitives
Duke University (via Coursera)
DeFi and the Future of Finance is a set of four courses that focus on decentralized finance. The second course is called DeFi Primitives. It is recommended that you take the first course, DeFi Infrastructure, before this course. In this course, we talk about transaction mechanics and introduce both fungible and non-fungible tokens – or NFTs. The course explores the important issue of custody (holding private keys). The course then explores supply adjustment which includes the minting and burning of tokens. The mechanics of bonding curves are introduced. The course then explores the role of direct as well as indirect incentives in the DeFi system. We then analyze swaps or decentralized exchange. We begin by contrasting DEX with centralized exchange (e.g., Coinbase or Binance). The course details the mechanics of Automated Market Makers and provides a number of detailed examples. There is a discussion of impermanent loss as well as (legal) front-running. We end the course by exploring both collateralized and flash loans.
Digital Transformation for Agile Organizations
Duke University (via Coursera)
In this course, you will learn how digital technologies are reshaping industries and creating new opportunities for agile organizations. You will explore the role of digital transformation in enhancing operational efficiency, driving innovation, and creating new business models. Through case studies, you’ll see how leading organizations have successfully leveraged technology to stay agile and competitive. This course is ideal for leaders seeking to harness the power of digital tools to create more adaptive and innovative organizations. Basic familiarity with digital trends will be helpful but is not required.
Pointers, Arrays, and Recursion
Duke University (via Coursera)
The third course in the specialization Introduction to Programming in C introduces the programming constructs pointers, arrays, and recursion. Pointers provide control and flexibility when programming in C by giving you a way to refer to the location of other data. Arrays provide a way to bundle data by guaranteeing sequences of data are grouped together. Finally, recursive functions—functions that call themselves—provide an alternative to iteration that are very useful for implementing certain algorithms.
Introduction to Genetics and Evolution
Duke University (via Coursera)
Introduction to Genetics and Evolution is a college-level class being offered simultaneously to new students at Duke University. The course gives interested people a very basic overview of some principles behind these very fundamental areas of biology. We often hear about new "genome sequences," commercial kits that can tell you about your ancestry (including pre-human) from your DNA or disease predispositions, debates about the truth of evolution, why animals behave the way they do, and how people found "genetic evidence for natural selection." This course provides the basic biology you need to understand all of these issues better, tries to clarify some misconceptions, and tries to prepare students for future, more advanced coursework in Biology (and especially evolutionary genetics). No prior coursework is assumed.
Increasing Real Estate Management Profits: Harnessing Data Analytics
Duke University (via Coursera)
In this final course you will complete a Capstone Project using data analysis to recommend a method for improving profits for your company, Watershed Property Management, Inc. Watershed is responsible for managing thousands of residential rental properties throughout the United States. Your job is to persuade Watershed’s management team to pursue a new strategy for managing its properties that will increase their profits. To do this, you will: (1) Elicit information about important variables relevant to your analysis; (2) Draw upon your new MySQL database skills to extract relevant data from a real estate database; (3) Implement data analysis in Excel to identify the best opportunities for Watershed to increase revenue and maximize profits, while managing any new risks; (4) Create a Tableau dashboard to show Watershed executives the results of a sensitivity analysis; and (5) Articulate a significant and innovative business process change for Watershed based on your data analysis, that you will recommend to company executives. Airbnb, our Capstone’s official Sponsor, provided input on the project design. The top 10 Capstone completers each year will have the opportunity to present their work directly to senior data scientists at Airbnb live for feedback and discussion. "Note: Only learners who have passed the four previous courses in the specialization are eligible to take the Capstone."
Introduction to Flask framework
Duke University (via Coursera)
In this 2-hour long project-based course, you will learn how to create a basic Flask web application, handle requests with route decorators, return responses, raise errors, and run the app locally for debugging. You will use Python packaging best-practices and will have a ready-to-use lab where you can practice what you've learned
Art of the MOOC: Experiments with Sound
Duke University (via Coursera)
Students of this course may try their hand at their own sound interventions and musical compositions, or simply focus on learning more about diverse musical traditions, sonic experimentation, and acoustic phenomena in everyday life. Designed by artist and Duke professor, Pedro Lasch, and UdK composer Mathias Hinke, this course is also co-taught by scholar and musician Jace Clayton (DJ Rupture) and curator Candice Hopkins (Documenta 14). The lectures link major artistic developments of recent decades to wider ideas about sound in specific social and spatial contexts. Also included are guest presentations from key thinkers and practitioners, like: Christopher DeLaurenti, Jen Delos Reyes, Tina Haver Currin, Quran Karriem, Christina Kubisch, Thomas Kusitzky, Scott Lindroth, Mark Anthony Neal, Bill Seaman, and John Supko. As the ‘ART of the MOOC’ title implies, learners and participants are encouraged to treat the MOOC itself as a public art medium. This happens mostly through the course’s optional practical components, local project productions, global exchanges, and critical feedback. While no prior sound production or musical experience is required, projects also offer challenging options for advanced learners. For other course offerings or language versions in this series, just search 'ART of the MOOC' in the Coursera catalog.
AI for Productivity
Duke University (via Coursera)
Work smarter, not harder, with AI This course will teach you, a working professional, how to boost your workflows with AI. You’ll learn how to identify, evaluate, and apply cutting-edge AI tools to streamline your daily tasks. Through case studies and discussions, you will analyze, apply, and get ready to create using tools such as ChatGPT, Copilot, Gemini, Notion, DALL·E, and Adobe Firefly, while learning to integrate AI responsibly into your professional routine. In Week 1, you’ll explore how to use AI writing assistants to draft, summarize, and refine communication. In Week 2, you’ll discover how to optimize AI for your planning, scheduling, and administrative needs, using Copilot and ChatGPT. In Week 3, you’ll learn how AI tools like Gemini and Insight can illuminate the insights in your information by organizing your notes or assisting with data-driven analysis. Finally, in Week 4, you’ll discover how to responsibly use AI to conduct ethical research and generate multimedia content using tools like Research Rabbit, Consensus, Stable Diffusion, Synthesia, and Runway. By the end of this course, you’ll be able to identify key AI use cases, compare tools that enhance productivity, and build AI-driven workflows that save time, spark innovation, and let you focus on meaningful, high-impact work.
Climate and Health for Healthcare Professions
Duke University (via Coursera)
What are the ways that climate change impacts human health? How can healthcare professionals support patients and communities to adapt to a changing climate? This short course explores the deep and complex connections between climate change and health for individuals and communities. By completing this course, students, trainees, practicing healthcare professionals and administrators will learn how to integrate climate awareness into their daily practice to inform and protect their patients and communities. While knowledge of human health is helpful, this is an introductory course with no required prerequisites. Climate change is the greatest threat to health in the 21st century, and it worsens existing inequities of health, security, and wellbeing. We’ll begin by addressing how human activity threatens planetary systems that support human health. We’ll then discuss the irony of how health systems, responsible for protecting health, also make these processes worse. To learn how to support patients and communities dealing with the impacts of climate change, you'll hear from a diverse group of healthcare experts who are already engaged in climate change and sustainability work. By the end of this course, you’ll gain skills to advocate for systems-level changes to mitigate climate change and support local resilience and adaptation. You’ll be given opportunities to think about how the concepts of this course can be applied to your own professional or personal context — no matter where you are in your healthcare career. By engaging with the intersection between climate and health, you will be more fully equipped to support your patients, colleagues, and community to build a more sustainable healthcare system.
Designing Larger Python Programs for Data Science
Duke University (via Coursera)
Modern programs are complicated structures, with hundreds to thousands of lines of code, but how do you efficiently move from smaller programs to more robust, complicated programs? How do data scientists simulate the randomness of real world problems in their programs? What techniques and best practices can you leverage to design pieces of software that can efficiently handle large amounts of data? In this course from Duke University, Python users will learn about how to create larger, multi-functional programs that can handle more complex tasks. We don't recommend that this be the first Python course you take, as we'll be covering a decent amount of specific programming syntax. However, if you hold a prerequisite knowledge of basic algebra, Python programming, and the Pandas library, you should be able to complete the material in this course. In the first module, we’ll discuss top-down design for larger programs, including the programming syntax and techniques that are useful to stitch together larger programs. Then in the following modules, we’ll transition into discussing Monte Carlo simulations and introduce you to the Poker project, the larger program you’ll create by the end of the course. By the end of this course, you should be able to decompose a programming problem into manageable pieces, explain the basics of Monte Carlo Methods, and efficiently integrate smaller pieces of code into a larger complete program. This will prepare you to take the next step in your data scientist journey, creating complex programs that can more creatively simulate real-world problems.
Telehealth: Head and Neck Assessment
Duke University (via Coursera)
Can telehealth provide an equally insightful physical assessment as a clinic visit? How complicated is it to perform a virtual head and neck assessment? In this course, we’ll be focusing on protocols and practical tips to conduct a reliable head and neck assessment remotely. We’ll build on the clinical knowledge you already possess and give helpful ways to modify your practice to suit the constraints of a telehealth video visit. This course will cover many of the typical physical assessments you would want to perform to diagnose complaints regarding the head, eyes, ears, nose, and throat (HEENT). We’ll provide patient management strategies and give you tools to consistently evaluate many HEENT complaints via telehealth. No matter how experienced you are in your practice or your specialty, this course contains pearls and pitfalls of telehealth virtual exams that can help improve your patients’ access to high-quality care. No previous telehealth or specific technology experience is required, though familiarity with physical assessments is assumed.
Introduction to Programming and Animation with Alice
Duke University (via Coursera)
This course is an introductory programming course that combines programming with animation, using the programming environment Alice. You will first learn to tell 3D animated stories by programming Aliceʼs 3D objects. In particular you will learn how to set up a scene, to tell a story using storyboarding, to move the camera, and how to move and rotate objects. You will learn programming concepts such as writing your own instructions, repetition, making decisions, and grouping similar objects together. In the second half of the course you will learn how to combine the topics you have learned with event programming to build 3D games you and your friends can play.
Purpose-Driven Leadership for Strategy and Innovation
Duke University (via Coursera)
In this course, you will explore how organizational purpose provides clarity and direction amidst uncertainty. Purpose acts as an anchor, offering shared meaning and a foundation for strategic thinking in complex environments. You will learn why a clear purpose is essential to solve significant challenges and seize opportunities, and how leaders can define and align their organization’s purpose with long-term goals. Practical examples will illustrate how purpose-driven leadership accelerates innovation and drives sustainable growth. This module is ideal for leaders who want to clarify their organization’s purpose and guide their teams through strategic transformation. No prior experience in purpose formulation is required.
핀테크 법률 및 정책
Duke University (via Coursera)
성공적인 핀테크 기업이 되기 위해서는 혁신적인 기술은 물론 해당 비즈니스에 적용되는 법률 및 규제를 이해해야 합니다. 이번 강좌를 통해 그와 관련된 지식을 얻을 수 있습니다. 먼저 암호화폐, 암호화폐 공모, 온라인 대출, 지급 및 자산 관리 신기술, 금융 계좌 집계소에 관련된 중요한 법률, 규제 및 정책 사안에 대해 알아보겠습니다. 아울러 미국 규제 기관들이 금융 신기술의 등장에 어떻게 적응을 지속해 나가는지 알아보고, 한 특정 기관이 핀테크 기업이 제도권 은행이 될 수 있도록 하기 위해 제시한 방안을 살펴보겠습니다. 또한 미국의 은행 규제에 대한 기본 사항도 살펴보겠습니다. 이러한 신기술이 낯설게 느껴지더라도 걱정하실 필요는 없습니다. 근간이 되는 기술에 대한 높은 수준의 개요로 매 강좌 섹션을 시작할 것이기 때문입니다. 본 강좌는 주로 미국 내 핀테크 산업에 초점을 두고 있지만 모든 관련 법률 및 규제 사안을 다룰 수는 없습니다. 따라서 본 강좌를 법률적 조언으로 받아들여서는 안 됩니다.본 강좌는 핀테크 기업들이 다양한 부문에서 직면하게 되는 핵심적인 법률 및 규제 사안과 워싱턴 D.C. 및 전국 주도에서 진행 중인 중요한 정책 토론에 대해 알아보는 것을 목표로 합니다.
Building Financial Models for Entrepreneurs
Duke University (via Coursera)
How much capital does an impact enterprise really need – and how do you figure that out? This self-paced, mini-MBA-style course walks any entrepreneur step-by-step through building a financial model using our Excel template. You will undertake a process to define your funding gap, test investment scenarios, and plan your future financing needs with confidence. You’ll learn how to input financial data, generate investor-ready projections, and calculate the funding gap—how much capital is needed to reach financial break-even. You’ll also learn how to pressure-test your projections to withstand investor scrutiny and model different types of investment offers, such as equity and debt. By experimenting with various scenarios, you’ll gain the skills to assess how new capital affects your financial outlook and how to negotiate terms that support your enterprise’s success. By the end of the course, you’ll be able to confidently interpret and explain financial projections, evaluate investment offers, and make informed decisions about raising capital. This course is ideal for anyone looking to understand entrepreneurial finance, financial projections, and modeling investment offers, regardless of background. No prior experience is required, as we break down complex concepts into clear, accessible language and provide practical tools and templates to support your learning.
Think Again III: How to Reason Inductively
Duke University (via Coursera)
Want to solve a murder mystery? What caused your computer to fail? Who can you trust in your everyday life? In this course, you will learn how to analyze and assess five common forms of inductive arguments: generalizations from samples, applications of generalizations, inference to the best explanation, arguments from analogy, and causal reasoning. The course closes by showing how you can use probability to help make decisions of all sorts. Suggested Readings Students who want more detailed explanations or additional exercises or who want to explore these topics in more depth should consult Understanding Arguments: An Introduction to Informal Logic, Ninth Edition, Concise, Chapters 8-12, by Walter Sinnott-Armstrong and Robert Fogelin. Course Format Each week will be divided into multiple video segments that can be viewed separately or in groups. There will be short ungraded quizzes after each segment (to check comprehension) and a longer graded quiz at the end of the course.
Stress First Aid for Healthcare Workers: A Peer Support Tool
Duke University (via Coursera)
Stress First Aid (SFA) is a peer support toolkit designed to preserve life, prevent further harm, and promote recovery. Stress First Aid offers a flexible menu of options for recognizing and addressing stress reactions. It can be used for self-care, to help co-workers with stress reactions, or to help someone seek other types of support. Stress First Aid is a framework of practical actions that can help reduce the likelihood that stress reactions will develop into more severe or long-term problems. Ideally everyone in an organization would learn the vocabulary and basics of Stress First Aid, to share a language and understanding of stress and stress injury. When everyone in an organization is trained in SFA, support could occur wherever and whenever it’s needed. Upon completion of Stress First Aid: A Peer Support Tool, you’ll be eligible for 9.00 credits (AMA PRA Category 1 Credit(s), ANCC, Attendance, JA-Credit-AH) through the Duke University Health System Clinical Education and Professional Development Office.
Gold Market Foundations
Duke University (via Coursera)
The value of all the gold in the world is $25 trillion – yet very few investors have gold in their portfolios. Ironically, gold is the oldest financial asset, but it is poorly understood and under-researched. There are many stories about gold, but very little evidence. This course provides the evidence. After completing the course, you will understand how gold performs during equity market turmoil and during inflation surges and its role in a diversified portfolio. The course explores the reasons why the gold price has recently surged by focusing on the financialization of gold, central bank accumulation, de-dollarization efforts, questions about the status of the U.S. dollar as a reserve currency, and the potential demand shock if gold is classified in a future version of Basel III as an asset commercial banks can hold for regulatory purposes (central banks hold gold as a reserve asset and it seems contradictory not to allow commercial banks to do the same). The Golden Dilemma framework is also introduced to credible future price paths for gold. Finally, the long-term prospects for gold are detailed, given expected technological innovations.
Telehealth Clinical Essentials
Duke University (via Coursera)
How can telehealth expand healthcare access to our patients? What are ways we can leverage telehealth to better help our patients? In this short introductory course, you’ll receive an introduction to telehealth basics geared toward any healthcare professional or student who has patient-facing clinical responsibilities. We’ll first begin with how you can set yourself, your team, and your patients up for success by using practical tips to ensure success before, during, and after telehealth video appointments. We’ll then discuss general telehealth assessments, focusing on how to work with your patients to assess their vital signs and cognitive function as well as how you can complete a virtual environmental assessment. No matter what speciality or stage you’re at in your healthcare professional journey, this course will help you develop practical skills to be applied to your practice. No previous telehealth or specific technology experience is required.
Nurturing Entrepreneurial Mindsets
Duke University (via Coursera)
Welcome to Nurturing Entrepreneurial Mindsets! In this course, we’ll see how Methodism’s history of entrepreneurism has fueled innovative ministries. We will consider how gifts of wisdom, virtue, and vision came from Wesley’s ministerial failure in Savannah, Georgia. Lastly, we will discuss how that spirit of innovation can help us faithfully meet our current moment. As we reflect on how we can nurture entrepreneurial mindsets wherever we are called to serve, we pray your discussions around these questions may be beneficial for your ministry. If you are a pastor or ministry professional in need of Continuing Education Unit (CEU) credits for your professional development, CEU credits are available for this course. Upon successful completion of this course, you can provide your Coursera certificate and the course description to your employer for recognition of earning 0.5 CEUs. Contact divinityonline@duke.edu with any questions regarding CEUs for this course. Each of the 5 courses in the Rediscovering the Heart of Methodism specialization is worth 0.5 CEUs, for a total of 2.5 CEUs for completing all of the courses. This course is part of the Rediscovering the Heart of Methodism series. This is one of five 4-week online courses designed to help engaged laypeople and clergy (including local pastors in licensing schools) develop core capacities for innovative leadership within the Wesleyan tradition. Through this series, we hope you will experience a deeper grounding in the distinctive elements of Methodism at its best, and a renewed capacity for hopeful, imaginative participation in the mission of God.
Beginning Llamafile for Local Large Language Models (LLMs)
Duke University (via Coursera)
Learners will gain the skills to serve powerful language models as practical and scalable web APIs. They will learn how to use the llama.cpp example server to expose a large language model through a set of REST API endpoints for tasks like text generation, tokenization, and embedding extraction. The course dives into the technical details of running the llama.cpp server, configuring various options to customize model behavior, and efficiently handling requests. Learners will understand how to interact with the API using tools like curl and Python, allowing them to integrate language model capabilities into their own applications. Throughout the course, hands-on exercises and code examples reinforce the concepts and provide learners with practical experience in setting up and using the llama.cpp server. By the end, participants will be equipped to deploy robust language model APIs for a variety of natural language processing tasks. The course stands out by focusing on the practical aspects of serving large language models in production environments using the efficient and flexible llama.cpp framework. It empowers learners to harness the power of state-of-the-art NLP models in their projects through a convenient and performant API interface.
Think Again IV: How to Avoid Fallacies
Duke University (via Coursera)
We encounter fallacies almost everywhere we look. Politicians, salespeople, and children commonly use fallacies in order to get you to think whatever they want you to think. It’s important to learn to recognize fallacies so that you can avoid being fooled by them. It’s also important to learn about fallacies so that you avoid making fallacious arguments yourself. This course will show you how to identify and avoid many of the fallacies that lead people astray. In this course, you will learn about fallacies. Fallacies are arguments that suffer from one or more common but avoidable defects: equivocation, circularity, vagueness, etc. It’s important to learn about fallacies so that you can recognize them when you see them, and not be fooled by them. It’s also important to learn about fallacies so that you avoid making fallacious arguments yourself. Suggested Readings Students who want more detailed explanations or additional exercises or who want to explore these topics in more depth should consult Understanding Arguments: An Introduction to Informal Logic, Ninth Edition, Concise, Chapters 13-17, by Walter Sinnott-Armstrong and Robert Fogelin. Course Format Each week will be divided into multiple video segments that can be viewed separately or in groups. There will be short ungraded quizzes after each segment (to check comprehension) and a longer graded quiz at the end of the course.
Python Essentials for MLOps
Duke University (via Coursera)
Python Essentials for MLOps (Machine Learning Operations) is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow. By the end of the course, learners will have the necessary skills to write Python scripts for automating common MLOps tasks. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their Python skills.
Pandas for Data Science
Duke University (via Coursera)
How can you effectively use Python to clean, sort, and store data? What are the benefits of using the Pandas library for data science? What best practices can data scientists leverage to better work with multiple types of datasets? In the third course of Data Science Python Foundations Specialization from Duke University, Python users will learn about how Pandas — a common library in Python used for data science — can ease their workflow. We recommend you should take this course after the first two courses of the specialization. However, if you hold a prerequisite knowledge of basic algebra, Python programming, and NumPy, you should be able to complete the material in this course. In the first week, we’ll discuss Python file concepts, including the programming syntax that allows you to read and write to a file. Then in the following weeks, we’ll transition into discussing Pandas more specifically and the pros and cons of using this library for specific data projects. By the end of this course, you should be able to know when to use Pandas, how to load and clean data in Pandas, and how to use Pandas for data manipulation. This will prepare you to take the next step in your data scientist journey using Python; creating larger software programs.
Creating an Impact Investment Ask
Duke University (via Coursera)
How does an impact entrepreneur make a compelling case for investment? This course teaches you how to assess a venture’s readiness for impact capital by examining two essential dimensions: business growth and impact. On the business side, you’ll use a diagnostic tool to evaluate seven key elements that drive growth and understand how investors assess profitability through unit economics. On the impact side, you’ll learn a four-step framework for building strong impact management practices that meet investor expectations. By the end of the course, you’ll know how to integrate these insights to clearly articulate and justify your capital ask confidently and credibly. This course is designed for aspiring and current impact entrepreneurs or managers, aspiring impact investors learning how to evaluate impact ventures, and any learner interested in how businesses can generate a positive impact. This course requires no prior experience. We break down complex ideas into accessible language, define key terms, and provide practical tools and templates to support your learning and application.
ART of the MOOC: Public Art and Pedagogy
Duke University (via Coursera)
Students of this course may try their hand at their own public art interventions, or simply focus on learning from the theory of public practice and its recent history. Designed by artist and Duke professor, Pedro Lasch, and co-taught by Creative Time artistic director, Nato Thompson, this course presents public culture and art in their radically reinenvented contemporary forms. The lectures link major developments of recent decades to wider topics like spatial politics, everyday social structures, and experimental education. Also included are guest presentations from key thinkers and practitioners, like: Tania Bruguera, Claire Doherty, Tom Finkelpearl, Hans Haacke, Shannon Jackson, Suzanne Lacy, Rick Lowe, and many more. As the ‘ART of the MOOC’ title implies, learners and participants are encouraged to treat the MOOC itself as a public art medium. This happens mostly through the course’s practical components, local project productions, global exchanges, and critical feedback. While no prior art making experience is required, projects also offer challenging options for advanced learners. For other course offerings or language versions in this series, just search 'ART of the MOOC' in the Coursera catalog.
Nanotechnology: A Maker’s Course
Duke University (via Coursera)
How can we create nano-structures that are 10,000 times smaller than the diameter of a human hair? How can we “see” at the nano-scale? Through instruction and lab demonstrations, in this course you will obtain a rich understanding of the capabilities of nanotechnology tools, and how to use this equipment for nano-scale fabrication and characterization. The nanoscale is the next frontier of the Maker culture, where designs become reality. To become a Nanotechnology Maker pioneer, we will introduce you to the practical knowledge, skills, and tools that can turn your nanotechnology ideas into physical form and that enable you to image objects at the nano-scale. This course has been developed by faculty and staff experts in nano-fabrication, electron beam microscopy, and nano-characterization through the Research Triangle Nanotechnology Network (RTNN). The RTNN offers training and use of the tools demonstrated in this course to schools and industry through the United States National Nanotechnology Coordinated Infrastructure program. The tools demonstrated in this course are available to the public through the RTNN.
Inferenzstatistik
Duke University (via Coursera)
This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data
Data Tidying and Importing with R
Duke University (via Coursera)
Build confidence working with messy, real-world data. In this course, you’ll learn how to import, clean, and organize data in R so that it’s ready for analysis, visualization, or modeling. Using dplyr, tidyr, and other Tidyverse tools, you’ll practice joining datasets, reshaping data, and creating efficient data pipelines that support reproducible work. You’ll also explore how to responsibly collect and scrape data from online sources, including ethical and legal considerations. By the end of this course, you’ll know how to transform raw datasets into structured, tidy formats and you’ll understand how responsible data handling and documentation are essential to high-quality, ethical data science.
신재생 에너지와 녹색기업가 정신
Duke University (via Coursera)
여러분 반갑습니다. 이번 강의에서는 에너지, 금융, 부동산, 설계, 공학, 환경 분야에서 새로운 사업을 시작하는 것을 배우고, 동시에 전 세계적으로 환경과 인체 건강에 긍정적인 영향을 줄 방법에 대한 도움을 받을 수 있습니다. 재생 에너지 및 그린빌딩 분야에서 변화를 만들고 부를 창출할 수 있는 직업의 일환으로 기업가 정신 분야에 관한 도구, 동향, 팁을 통합적으로 알아볼 예정이며, 도구, 동향, 팁을 통합적으로 알아볼 예정이며,이론을 배우기 위한 과정이 아닙니다.이 강의는 실제 적용 사례, 단계별 조언, 사례 연구에 초점을 맞췄습니다. 이 강의를 마치고 나면, 학생은 다음을 수행할 수 있습니다. 재생 에너지 및 그린빌딩 분야의 핵심적인 비즈니스 기회, 도전, 잠재적 해답 정의하기 재생 에너지 또는 그린빌딩에 관한 성공적인 비즈니스 분석하기 재생 에너지 또는 그린 빌딩 제품 및 서비스로 해결할 수 있는 문제 2~3가지 찾기 새로운 비즈니스에 자금을 제공해줄 수 있는 투자자와 만날 계획하기 1페이지짜리 비즈니스 아이디어 요약 템플릿과 Business Model Canvas로 나만의 새로운 비즈니스 아이디어를 만들고 구체화해서 새로운 비즈니스 또는 기업을 만들기 위한 첫 번째 발걸음 내딛기
Agile Dashboards for Data-Driven Decision-Making
Duke University (via Coursera)
In this course, you will learn how to build and utilize agile dashboards that provide real-time insights into your organization’s performance. You will explore key performance metrics, financial levers, and tools that can help leaders quickly assess their business’s health and make informed decisions to maintain agility. The agile dashboard is a critical tool for leaders who need to drive quick, informed decision-making in an ever-changing business environment. This course is suitable for managers and leaders looking to enhance their decision-making capabilities through agile data-driven tools. No prior experience with dashboards or data science is required.
Gold and Bitcoin
Duke University (via Coursera)
Gold and Bitcoin demystifies two monetary assets with data. You’ll learn how bitcoin works—blockchains, hashing, mining, keys, and transactions—and why decentralization matters. Then we compare gold and bitcoin where they are similar—scarcity, low inflation, high production cost, and absent cash flows—and where they diverge: custody, divisibility, auditability, settlement, censorship resistance, volatility, market size, and institutional adoption. We connect market structure to portfolio design, showing when each asset helps during equity drawdowns or inflation shocks. You’ll also understand today’s price drivers: financialization (ETFs, tokenized gold), central-bank accumulation, de-dollarization, and reserve-currency politics, plus a policy wildcard—potential Basel III treatment of gold as a high-quality liquid asset. Finally, we confront tail risks: bitcoin’s 51% and quantum threats and gold’s technological supply shocks (advanced extraction, modern alchemy, and off-world sources). Throughout, we use the golden-constant and Golden Dilemma frameworks to anchor valuation and build scenarios. Leave with clear, evidence-based answers and practical allocation tools you can apply immediately.
R을 사용한 확률 및 데이터 소개
Duke University (via Coursera)
이 과정에서는 데이터 표본 추출 및 탐색, 기본 확률 이론 및 베이즈 정리를 소개합니다. 다양한 유형의 표본 추출 방법을 검토하고 이러한 방법이 추론 범위에 어떤 영향을 미칠 수 있는지 논의합니다. 수치 요약 통계 및 기본 데이터 시각화를 포함하여 다양한 탐색적 데이터 분석 기술을 다룹니다. R 및 RStudio(무료 통계 소프트웨어)를 설치하고 사용하는 방법을 안내하고 이 소프트웨어를 실습 및 최종 프로젝트에 사용합니다. 이 과정의 개념과 기술은 전문화 과정의 추론 및 모델링 과정을 위한 빌딩 블록 역할을 합니다.
Cloud Computing Foundations
Duke University (via Coursera)
Welcome to the first course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to build foundational Cloud computing infrastructure, including websites involving serverless technology and virtual machines. You will also learn how to apply Agile software development techniques to projects which will be useful in building portfolio projects and global-scale Cloud infrastructures. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a statically hosted website using the Hugo framework, AWS Code Pipelines, AWS S3 and GitHub.
Practical Python: Start Your Programming Journey
Duke University (via Coursera)
Have you ever wanted to learn programming, where you get to write programs tailored to your interests? How about learning to code while also learning how to design, plan, and implement your projects? If yes, welcome to "Practical Python: Starting Your Programming Journey!" In this course, we teach you the beginnings of Python programming while assuming you are starting with no experience. By the end of this course, you will be able to write your own text adventure game, create a personalized calculator, write a poem, and so much more! This course will also introduce you to a process for planning out your programming projects and ideas on how to fix your code when it is not doing what you want. And we will teach you all of this through open-ended assignments that let you decide how to show us what you have learned! Most of our coding assignments have a small set of checks on your code, but otherwise, you get to decide what it does! Want to write code that generates a haiku? You can! Want to write code that generates song lyrics instead? You will get to do that by just week two of the course!
Telehealth: Musculoskeletal Assessment
Duke University (via Coursera)
What role do virtual musculoskeletal assessments play in patient care? What are the benefits of virtual assessments, and what virtual findings should prompt an in-person evaluation? In this short course, we’ll discuss when it is appropriate to conduct a virtual musculoskeletal assessment as well as tips and tricks to make these visits beneficial to both you and your patients. We’ll build on the clinical knowledge you already possess and give helpful ways to modify your in-person exam skills to have clinical value in the context of a telehealth visit. This course will begin by discussing a general musculoskeletal functional assessment before diving deeper into both upper and lower extremity joint assessment. We’ll discuss how you can properly coach patients to perform the proper maneuvers for joint assessment. No matter if you’re experienced in the field or a healthcare student interested in musculoskeletal assessment, this course introduces you to virtual physical assessments. By taking this course, you can contribute to broadening access to musculoskeletal healthcare. No previous telehealth or specific technology experience is required, though familiarity with physical assessments is assumed.
Open Source LLMOps Solutions
Duke University (via Coursera)
Learn the fundamentals of large language models (LLMs) and put them into practice by deploying your own solutions based on open source models. By the end of this course, you will be able to leverage state-of-the-art open source LLMs to create AI applications using a code-first approach. You will start by gaining an in-depth understanding of how LLMs work, including model architectures like transformers and advancements like sparse expert models. Hands-on labs will walk you through launching cloud GPU instances and running pre-trained models like Code Llama, Mistral, and stable diffusion. The highlight of the course is a guided project where you will fine-tune a model like LLaMA or Mistral on a dataset of your choice. You will use SkyPilot to easily scale model training on low-cost spot instances across cloud providers. Finally, you will containerize your model for efficient deployment using model servers like LoRAX and vLLM. By the end of the course, you will have first-hand experience leveraging open source LLMs to build AI solutions. The skills you gain will enable you to further advance your career in AI.
Negotiating with Impact Investors
Duke University (via Coursera)
How do you close a successful financing deal with impact investors? This course guides you through a step-by-step approach to effectively engage, pitch, and negotiate with impact investors. You’ll learn how to craft a cohesive investment narrative and align your emails, executive summary, and pitch deck around a clear investment story that balances financial return with social or environmental impact. You'll gain insight into the due diligence process, including what investors are looking for and where you have leverage. Finally, you'll explore common investment terms in impact deals and learn how to identify areas for negotiation to ensure a strong, long-term partnership. By the end of this course, you’ll be equipped to approach investors with confidence, communicate your value clearly, navigate due diligence efficiently, and negotiate terms that support your venture’s success. This course is ideal for aspiring and current impact entrepreneurs preparing to raise capital, advisors supporting impact ventures, and anyone interested in the mechanics of impact investing. No prior experience is required; we simplify complex concepts, define key terms, and provide practical tools and templates to support your learning and application.
برمجة Java: إنشاء نظام ترشيح
Duke University (via Coursera)
هل تساءلت يومًا كيف يختار Netflix الأفلام التي يرشحها لك؟ أو كيف يرشح لك Amazon الكتب؟ يمكننا معرفة كيفية عمل ذلك من خلال إنشاء مرشِح مبسّط خاص بنا! في هذا المساق التكميلي، ستعرض مهاراتك في حل المشكلات وبرمجة Java من خلال إنشاء أنظمة المرشِح. ستتعامل مع بيانات الأفلام، والتي تتضمن التقييمات، ولكن المبادئ المُتَضمَنة يمكن تكييفها بسهولة مع الكتب والمطاعم وغير ذلك. ستكتب برنامجًا يجيب على أسئلة خاصة بالبيانات، بما في ذلك أي عناصر ينبغي ترشيحها إلى المستخدم بناءً على تقييمه لعدة أفلام. مع وجود ملفات الإدخال الخاصة بتقييمات المستخدمين وعناوين الأفلام، ستتمكن من: 1. تسجيل البيانات وتحليلها إلى قوائم وخرائط؛ 2. حساب متوسط التقييمات؛ 3. حساب مدى تشابه مقيّم معين مع مستخدم آخر بناءً على التقييمات؛ و 4. ترشيح الأفلام إلى مستخدم معين بناءً على التقييمات. 5. عرض الأفلام المرشَحة لمستخدم معين على صفحة الويب.
Introduction to Retrieval Augmented Generation (RAG)
Duke University (via Coursera)
In this 2-hour project-based course, you will learn how to import data into Pandas, create embeddings with SentenceTransformers, and build a retrieval augmented generation (RAG) system with your data, Qdrant, and an LLM like Llamafile or OpenAI. This hands-on course will teach you to build an end-to-end RAG system with your own data using open source tools for a powerful generative AI application.
Setup Python
Duke University (via Coursera)
In this 2-hour long project-based course, you will learn how to: Describe the purpose of virtual environments in Python development Explain how to create and activate a virtual environment using the venv module Install packages and dependencies into a virtual environment using pip and requirements.txt. Completing this project on setting up Python environments will provide learners with essential skills for professional Python development. Learning to properly manage dependencies is crucial for any programmer. This project stands out by using current best practices for Python packaging, avoiding deprecated approaches. Learners will benefit from gaining hands-on experience with critical tools like virtual environments, pip, and pyproject.toml. Following the opinionated recommendations in this project will equip learners with a streamlined workflow for configuring reproducible and isolated Python environments. The project uniquely focuses on real-world developer needs, not just toy examples. Learners will complete the project knowing how to dependency manage projects of any size for both dev and production. These professional techniques will enable learners to use Python for building robust applications across many domains.
Local LLMs with llamafile
Duke University (via Coursera)
In this 1-hour project-based course, you will learn to: Package open-source AI models into portable llamafile executables Deploy llamafiles locally across Windows, macOS and Linux Monitor system metrics like GPU usage when running models Query llamafile APIs with Python to process generated text * Experience real-time inference through hands-on examples
Space Medicine
Duke University (via Coursera)
Have you ever wondered what it would take for humans to travel beyond the comforts of our home planet, Earth? You are invited to join us in Space Medicine - an online experience facilitated by two recent Duke graduates in which you will learn about and engage in the most pressing medical challenges facing NASA and others advancing the future of space exploration. Space Medicine is a free, non-certificate course featuring interactive modules and weekly live discussions. Participants will reflect on questions pertinent to the future of human health in space, such as: How do humans respond to extreme environments? How can engineers, doctors, and scientific researchers come together to prevent space related health issues before they occur? If future generations of humans attempt to live in space, what challenges will they face? Which evolutionary adaptations to living on Earth are useful to surviving a months- or years-long voyage? No prior experience in science or medicine is required, as life science concepts will be introduced as necessary. At the end of the course, you will have gained valuable experience in applying modern medicine to space-based situations, from space flight to journeying to Mars.
How to Prioritize ESG Initiatives
Duke University (via Coursera)
This course introduces participants to ESG materiality and provides the tools needed to prioritize impactful initiatives. Learners will explore the concept of materiality, understand its significance in ESG practices, and gain practical skills to conduct Materiality Assessment Matrices. With a focus on asking the right questions and using essential tools, this course equips professionals to align ESG initiatives with organizational goals and drive meaningful outcomes.
End to End LLMs with Azure
Duke University (via Coursera)
This comprehensive course equips you with skills to leverage Azure for building and deploying Large Language Model (LLM) applications. Learn to use Azure OpenAI Service for deploying LLMs, utilizing inference APIs, and integrating with Python. Explore architectural patterns like Retrieval-Augmented Generation (RAG) and Azure services like Azure Search for robust applications. Gain insights into streamlining deployments with GitHub Actions. Apply your knowledge by implementing RAG with Azure Search, creating GitHub Actions workflows, and deploying end-to-end LLM applications. Develop a deep understanding of Azure's ecosystem for LLM solutions, from model deployment to architectural patterns and deployment pipelines.
Managing Big Data with MySQL
Duke University (via Coursera)
This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data by yourself! By the end of this course, you will have a clear understanding of how relational databases work, and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world.
人体生理学导论（中文版）
Duke University (via Coursera)
在本课程中，学生将学习认识和应用说明人体九个器官系统中整体人体机能（作为完整有机体）的基本概念。
Java Programming: Build a Recommendation System
Duke University (via Coursera)
Ever wonder how Netflix decides what movies to recommend for you? Or how Amazon recommends books? We can get a feel for how it works by building a simplified recommender of our own! In this capstone, you will show off your problem solving and Java programming skills by creating recommender systems. You will work with data for movies, including ratings, but the principles involved can easily be adapted to books, restaurants, and more. You will write a program to answer questions about the data, including which items should be recommended to a user based on their ratings of several movies. Given input files on users ratings and movie titles, you will be able to: 1. Read in and parse data into lists and maps; 2. Calculate average ratings; 3. Calculate how similar a given rater is to another user based on ratings; and 4. Recommend movies to a given user based on ratings. 5. Display recommended movies for a given user on a webpage.
Bayesian Statistics
Duke University (via Coursera)
This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution. Additionally, the course will introduce credible regions, Bayesian comparisons of means and proportions, Bayesian regression and inference using multiple models, and discussion of Bayesian prediction. We assume learners in this course have background knowledge equivalent to what is covered in the earlier three courses in this specialization: "Introduction to Probability and Data," "Inferential Statistics," and "Linear Regression and Modeling."
GenAI Basics - How LLMs Work
Duke University (via Coursera)
This is a one-hour course for nontechnical audiences so they can understand how GenAI models are trained with the basics of the data science process through a simple interactive demo where they don't have to install or download any software.
English Composition I
Duke University (via Coursera)
You will gain a foundation for college-level writing valuable for nearly any field. Students will learn how to read carefully, write effective arguments, understand the writing process, engage with others' ideas, cite accurately, and craft powerful prose. Course Learning Objectives • Summarize, analyze, question, and evaluate written and visual texts • Argue and support a position • Recognize audience and disciplinary expectations • Identify and use the stages of the writing process • Identify characteristics of effective prose • Apply proper citation practices • Discuss applying your writing knowledge to other writing occasions
Customer-Centric Innovation
Duke University (via Coursera)
In this course, you will explore how to develop agile business strategies focused on delivering value to customers in dynamic markets. You will learn techniques to foster customer-driven innovation, incorporating customer insights into strategic decisions and product development. Additionally, the course will focus on creating customer-centric organizations that are agile, responsive, and capable of evolving with market needs. This course is perfect for leaders and product managers looking to improve customer engagement through innovation. No prior experience in customer strategy is needed, though a background in business leadership will be beneficial.
Web Scraping with Python
Duke University (via Coursera)
In this 2-hour long project-based course, you will learn how to analyze complex HTML structures and identify the relevant data to be extracted using Scrapy and XPath. You will apply the concepts of web scraping, including setting up a Scrapy project, generating spiders, and using XPath queries to extract data from websites that do not provide an API. Additionally, you will evaluate the effectiveness and efficiency of your scraping code, considering factors such as changing webpage structures, scalability, and coding defensively to ensure robustness. The course includes hands-on labs where you will create a spider and parse complex HTML, allowing you to practice and reinforce the concepts learned.
برمجة Java: حل المشكلات باستخدام البرامج
Duke University (via Coursera)
تَعلّم التعليمات البرمجية في Java، وحسّن برمجتك ومهارات حل المشكلات. ستتعلم تصميم الخوارزميات وأيضًا تطوير البرامج وتصحيحها. استخدام فئات مخصصة مفتوحة المصدر، ستكتب برامج بإمكانها الوصول إلى الصور ومواقع الويب وأنواع أخرى من البيانات وتحولها. في نهاية الدورة ستنشئ برنامجًا يُحدد شهرة أسماء المواليد المختلفة في US بمرور الوقت من خلال تحليل ملفات القيمة المفصولة بفاصلة (CSV). بعد الانتهاء من الدورة ستتمكن من: 1. تحرير برنامج Java وتحويله برمجيًا وتشغيله، 2. استخدام العبارات الشرطية وحلقات التكرار في برنامج Java، 3. استخدام وثائق Java API في كتابة البرامج. 4. تصحيح برنامج Java باستخدام أسلوب علمي، 5. كتابة أسلوب Java لحل مشكلة معينة، 6. تطوير مجموعة من حالات الاختبار كجزء من تطوير البرنامج، 7. إنشاء فئة باستخدام عدة أساليب تعمل معًا لحل المشكلة، و 8. استخدام تقنيات تصميم فرق تسد لبرنامج يستخدم عدة أساليب.
Understanding 9/11: Why 9/11 Happened & How Terrorism Affects Our World Today
Duke University (via Coursera)
This course will explore the forces that led to the 9/11 attacks and the policies the United States adopted in response. We will examine the phenomenon of modern terrorism, the development of the al Qai'da ideology, and the process by which individuals radicalize towards violence.
Inferential Statistics
Duke University (via Coursera)
This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data
Forming Christ-Shaped Leaders
Duke University (via Coursera)
Welcome to Forming Christ-Shaped Leaders. This course is part of the Rediscovering the Heart of Methodism series. Through this series, we hope you will experience a deeper grounding in the distinctive elements of Methodism at its best, and a renewed capacity for hopeful, imaginative participation in the mission of God. This course addresses two closely related questions: what does it mean to be a Christ-shaped leader, and how do we become that kind of leader? To develop our answers, we’ll mine the riches of Wesleyan wisdom, Mary’s witness, and Jesus’s teachings. We’ll also consider how calling and trauma inform Christian leadership. These four weeks will provide frameworks to guide our ongoing formation as Christ-shaped leaders who, in turn, encourage that same growth in others. If you are a pastor or ministry professional in need of Continuing Education Unit (CEU) credits for your professional development, CEU credits are available for this course. Upon successful completion of this course, you can provide your Coursera certificate and the course description to your employer for recognition of earning 0.5 CEUs. Contact divinityonline@duke.edu with any questions regarding CEUs for this course. Each of the 5 courses in the Rediscovering the Heart of Methodism specialization is worth 0.5 CEUs, for a total of 2.5 CEUs for completing all of the courses.
Rust for Large Language Model Operations (LLMOps)
Duke University (via Coursera)
Do you aspire to be a Rust developer at the forefront of the AI revolution? This groundbreaking course is designed specifically to train you in Large Language Model Operations (LLMOps) using Rust. This course doesn't just scratch the surface; it takes a deep dive into how you can integrate Rust with sophisticated LLM frameworks like HuggingFace Transformers. We'll also explore how to effectively deploy these large models on cloud infrastructures such as AWS, all while incorporating DevOps methodologies tailored for LLMOps.
데이터 중심 기업을 위한 비즈니스 지표
Duke University (via Coursera)
이 과정에서는 데이터 분석을 사용하여 회사의 경쟁력과 수익성을 높이는 방법에 대한 모범 사례를 배웁니다. 가장 중요한 비즈니스 지표를 인식하고 단순한 데이터와 구별할 수 있습니다. 다양한 유형의 회사에서 수행하는 비즈니스 분석가, 비즈니스 데이터 분석가 및 데이터 과학자의 중요하면서도 다른 역할을 명확하게 이해할 수 있습니다. 그리고 수요가 높은 이러한 직종에 취업하고 성공하기 위해 필요한 기술을 정확히 파악하게 됩니다. 마지막으로 이 과정에서 제공되는 체크리스트를 사용하여 기업이 빅 데이터 문화를 얼마나 효과적으로 수용하고 있는지 점수를 매길 수 있습니다. 아마존, 우버 및 에어비앤비와 같은 디지털 회사는 빅 데이터를 창의적으로 사용하여 전체 산업을 변화시키고 있습니다. 이러한 회사가 와해적인 이유와 어떻게 데이터 분석 기술을 사용하여 기존 회사를 앞서가는지를 알 수 있습니다.
GenAI and LLMs on AWS
Duke University (via Coursera)
This course will teach you how to deploy and manage large language models (LLMs) in production using AWS services like Amazon Bedrock. By the end of the course, you will know how to: Choose the right LLM architecture and model for your application using services. Optimize cost, performance and scalability of LLMs on AWS using auto-scaling groups, spot instances and container orchestration Monitor and log metrics from your LLM to detect issues and continuously improve quality Build reliable and secure pipelines to train, deploy and update models using AWS services Comply with regulations when deploying LLMs in production through techniques like differential privacy and controlled rollouts This course is unique in its focus on real-world operationalization of large language models using AWS. You will work through hands-on labs to put concepts into practice as you learn. Whether you are a machine learning engineer, data scientist or technical leader, you will gain practical skills to run LLMs in production.
Chimpanzee Behavior and Conservation
Duke University (via Coursera)
Chimpanzees are one of our closest living relatives, yet almost nothing was known about their behavior in the wild until Jane Goodall started her groundbreaking study of the chimpanzees of Gombe, Tanzania in 1960. This study continues today, following the same chimpanzee families that Jane Goodall first encountered over 55 years ago. Guided by three course instructors who have lived and worked with the Gombe chimpanzees, you will learn how Goodall’s early discoveries changed our view of human uniqueness. By completing the course, you will gain a new appreciation of the deep similarities between chimpanzees and humans in intelligence, tool use, hunting, personality and social relationships, as well as some key differences. You will learn how chimpanzees interact with their environment and how their behavior is influenced by ecology, as well as the severe conservation challenges they face today. And you will employ your new knowledge of chimpanzees to construct a persuasive argument for their protection. This course is open to everyone interested in learning more about these fascinating and complex beings. Knowledge of high-school level biology is beneficial but not required. Please keep in mind, however, that the content of this course will cover all aspects of chimpanzee life, including scientific discussion of sexual and aggressive behaviors.
ESG Value Creation for Business Impact
Duke University (via Coursera)
This course examines how Environmental, Social, and Governance (ESG) principles create value for businesses, society, and the planet. Participants will delve into key environmental, social, and governance factors—such as climate change, resource efficiency, employee welfare, and corporate ethics—and learn to advocate for ESG adoption. By identifying the most relevant ESG priorities for their organization, learners will gain practical strategies to foster meaningful change and promote sustainable business values across industries.
Open Design
Duke University (via Coursera)
What is design? How is it a deeply human endeavor? How can we design better products, services, and experiences in our communities? If you’re interested in helping create a more equitable and accessible world, this Center for Computational Thinking module on Open Design is for you. In this introductory module to Open Design, you’ll learn how you can center equity in your design processes. You’ll learn how the iterative four mindsets of Open Design — understand, create, evaluate, and share — will guide you to meaningfully impact your community. The principles at the heart of Open Design — active inclusivity, transparency, and collaboration — are applicable to work in all fields, providing you with a reflective framework as you make important decisions. This module provides the background on Open Design and its relationship to similar methodologies. After completing this introductory module, you should have the knowledge necessary to explain Open Design to others — and continue your Open Design journey with other learning opportunities.
Sports and Society
Duke University (via Coursera)
Sports play a giant role in contemporary society worldwide. But few of us pause to think about the larger questions of money, politics, race, sex, culture, and commercialization that surround sports everywhere. This course draws on the tools of anthropology, sociology, history, and other disciplines to give you new perspectives on the games we watch and play. It's the new and improved version of Professor Orin Starn's original "Sports and Society" for Coursera, which drew more than 40,000 students. We will focus on both popular sports like soccer (or “football,” as anyone outside America calls it), basketball, and baseball, and also lesser-known ones like mountain-climbing and fishing. You will never watch or think about sports in the same way again.
Interacting with the System and Managing Memory
Duke University (via Coursera)
The final course in the specialization Introduction to Programming in C will teach you powerful new programming techniques for interacting with the user and the system and dynamically allocating memory. You will learn more sophisticated uses for pointers, such as strings and multidimensional arrays, as well as how to write programs that read and write files and take input from the user. Learning about dynamic memory allocation will allow your programs to perform complex tasks that will be applied in the final part of the specialization project: a Monte Carlo simulation for calculating poker hand probabilities.
Environmental Leadership
Duke University (via Coursera)
What does it mean to be an environmental leader? How can we inspire others to achieve common goals to combat challenges like climate change? This short course provides an entry-level overview of timeless and timely leadership principles and how to apply them to environmental contexts in your own life. No matter your interests, age, career, or goals, you can make a difference. No prerequisites are needed for this course. To combat climate change, protect our environment, and develop sustainable communities, we must all engage in environmental leadership. Addressing today’s complex environmental issues requires us to view leadership less as a responsibility associated with any one position or person, and rather a call for collective action. Through this course, you will learn how to develop competencies and relationships that will help you work with others to understand the interconnectedness of systems and accomplish goals across boundaries. All kinds of leaders are needed to tackle the environmental and climate challenges that we face as a global society. By the end of the course, you will explore concepts of environmental leadership and how you might apply them in your own community or organization. By growing your leadership skills, you will be more fully equipped to work with others to pave the way to a just and sustainable future.
Python Decorator Functions
Duke University (via Coursera)
In this 1-hour hands-on Python programming project, you will learn how to use decorators to modify behaviors of functions without changing the source code. You’ll study common use cases like timing, logging, caching and more. By the end, you’ll be able to transparently add features to functions using custom decorators.
Linux and Bash for Data Engineering
Duke University (via Coursera)
In this second course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn the fundamentals of Linux necessary to perform data engineering tasks. Additionally, you will explore how to use both Bash and zsh configurations, and develop the syntax needed to interact and control Linux. These skills will allow you to manage and manipulate databases in a Bash environment.
ESG Mindsets for Business Transformation
Duke University (via Coursera)
This course explores the transformative power of adopting the right mindsets for successful ESG implementation. Participants will discover solution-focused perspectives essential for tackling challenges and shifting toward sustainable thinking. By developing adaptability and strategic thinking, learners will be equipped to lead impactful change and align their actions with Environmental, Social, and Governance (ESG) principles in today’s evolving business landscape.
Rediscovering Wesleyan Mission
Duke University (via Coursera)
We invite you to join Duke Divinity School in “Rediscovering Wesleyan Mission,” the second of five courses in the Rediscovering the Heart of Methodism series, designed to help engaged laypeople and clergy (including local pastors in licensing schools) develop core capacities for innovative leadership within the Wesleyan tradition. This course is designed to help individuals and Christian communities rediscover the Wesleyan mission at its finest. It introduces Methodism’s history as a missionary movement and teaches us to recenter our histories within the story of God’s mission to the world. In addition, it explores key practices and commitments that undergird a Methodist sense of mission, including convictions about salvation. Above all, it gives us opportunities to attend to the Holy Spirit and discern how God may be prompting us and our communities to engage in mission today. If you are a pastor or ministry professional in need of Continuing Education Unit (CEU) credits for your professional development, CEU credits are available for this course. Upon successful completion of this course, you can provide your Coursera certificate and the course description to your employer for recognition of earning 0.5 CEUs. Contact divinityonline@duke.edu with any questions regarding CEUs for this course. Each of the 5 courses in the Rediscovering the Heart of Methodism specialization is worth 0.5 CEUs, for a total of 2.5 CEUs for completing all of the courses. Each course includes four weeks of interactive video lessons from Duke Divinity School faculty and Methodist leaders, plus an interactive course workbook PDF that includes exercises to accompany each video lesson and discussion guides for group meetings.
MySQL-for-Data-Engineering
Duke University (via Coursera)
In this 2 hour project, you will get hands-on practice with MySQL for data engineering tasks. You will learn how to interact with MySQL databases from the command line interface, import and modify external datasets, integrate MySQL with Python applications, and more. By the end, you will have practical experience with essential MySQL skills needed for manipulating, processing, and working with relational databases in a data engineering context.
Impact Investment Finance
Duke University (via Coursera)
What are impact investors looking for? This course offers a practical introduction to the impact investing marketplace. You’ll learn how the market is structured, including the roles of asset owners and asset managers, and how capital flows between them. The course explores how impact investors pursue both financial and social or environmental returns, and the different types of investors involved along with their motivations, constraints, and preferred investment vehicles. You’ll hear directly from impact enterprise leaders about their experiences raising capital, and from investors about what they look for when evaluating opportunities. The course also highlights common mistakes enterprises make when seeking funding and offers strategies to attract aligned capital. By the end of this course you’ll be able to identify an effective impact investing strategy, and be prepared to start your journey in the impact marketplace. This course requires no prior knowledge and is designed for anyone interested in impact investing: whether you're an aspiring investor, an enterprise leader, or exploring a career in the field. We break down key concepts, explain investor types in accessible language, and define essential financial terms.
Data Modeling and Prediction with R
Duke University (via Coursera)
Learn how to move from exploring data to modeling it with confidence. In this course, you’ll build and interpret linear and logistic regression models in R to uncover relationships, make predictions, and quantify uncertainty. You’ll begin by learning how to fit and interpret simple and multiple linear regression models, then advance to modeling categorical outcomes with logistic regression. Finally, you’ll explore bootstrapping and hypothesis testing to understand and communicate the uncertainty in your results. By the end of this course, you’ll be able to use statistical modeling to make and explain data-driven decisions – an essential skill for data scientists, analysts, and anyone working with real-world data.
MLOps Platforms: Amazon SageMaker and Azure ML
Duke University (via Coursera)
In MLOps (Machine Learning Operations) Platforms: Amazon SageMaker and Azure ML you will learn the necessary skills to build, train, and deploy machine learning solutions in a production environment using two leading cloud platforms: Amazon Web Services (AWS) and Microsoft Azure. This course is also a great resource for individuals looking to prepare for AWS or Azure machine learning certifications or who are working (or seek to work) as data scientists, software engineers, software developers, data analysts, or other roles that use machine learning. Through a series of hands-on exercises, you will gain an intuition for basic machine learning algorithms and practical experience working with these leading Cloud platforms. By the end of the course, you will be able to deploy machine learning solutions in a production environment using AWS and Azure technology. Week 1. Explore data engineering with AWS technology. We’ll discuss topics such as getting started with machine learning on AWS, creating data repositories, and identifying and implementing solutions for data ingestion and transformation. Week 2. Gain basic data science skills with AWS technology. You will learn data cleaning techniques, perform feature engineering, data analysis, and data visualization for machine learning. We’ll prioritize using serverless solutions that are available on AWS to make the process more efficient. Week 3. Learn machine learning models with AWS technology. We’ll examine how to select appropriate models for the task at hand, choose hyperparameters, train models on the platform, and evaluate models. Week 4. Learn MLOps with AWS: the final phase of putting machine learning into production. We’ll discuss topics such as operationalizing a machine learning model, deciding between CPU and GPU, and deploying and maintaining the model. Week 5. Learn how to work with data and machine learning in a second leading Cloud-based platform: Azure ML.
Data Visualization and Transformation with R
Duke University (via Coursera)
Learn the foundations of data science by exploring, transforming, and visualizing data with R. In this course, you’ll develop core skills in exploratory data analysis and statistical thinking including: using visualizations to uncover patterns, identifying trends, and generating insights. You’ll gain hands-on experience with Tidyverse packages in R, work in RStudio, and create reproducible reports with Quarto. Along the way, you’ll also learn version control practices with Git and GitHub to document and share your work. By the end of this course, you’ll be able to transform and summarize data, craft clear and informative graphics, and communicate your findings through professional, reproducible workflows - laying the groundwork for all your future data science projects.
Data Science for Agile Decision-Making
Duke University (via Coursera)
This course focuses on how data science can be used to make more informed and agile business decisions. You will learn how to collect, analyze, and interpret data to drive insights and create business value. Through practical applications, you will explore how organizations use data to anticipate market changes, optimize operations, and enhance decision-making processes. This course is perfect for business leaders, managers, and decision-makers looking to use data more effectively. Basic knowledge of data analysis will be helpful, but not required.
Foundations of Local Large Language models
Duke University (via Coursera)
By the end of this course, a learner will have a solid understanding of Large Language Models running locally. You'll be able to setup a local environment using powerful tooling to run different LLMs and interact with them both with a web interface as well as with APIs. You will explore other tools and programming languages to interact with these LLMs and using LLMs via via Hugging Face Candle and Mozilla llamafile.
Operationalizing LLMs on Azure
Duke University (via Coursera)
This course is designed for individuals at both an intermediate and beginner level, including data scientists, AI enthusiasts, and professionals seeking to harness the power of Azure for Large Language Models (LLMs). Tailored for those with foundational programming experience and familiarity with Azure basics, this comprehensive program takes you through a four-week journey. In the first week, you'll delve into Azure's AI services and the Azure portal, gaining insights into large language models, their functionalities, and strategies for risk mitigation. Subsequent weeks cover practical applications, including leveraging Azure Machine Learning, managing GPU quotas, deploying models, and utilizing the Azure OpenAI Service. As you progress, the course explores nuanced query crafting, Semantic Kernel implementation, and advanced strategies for optimizing interactions with LLMs within the Azure environment. The final week focuses on architectural patterns, deployment strategies, and hands-on application building using RAG, Azure services, and GitHub Actions workflows. Whether you're a data professional or AI enthusiast, this course equips you with the skills to deploy, optimize, and build robust large-scale applications leveraging Azure and Large Language Models.
Understanding Stablecoins
Duke University (via Coursera)
Stablecoins have emerged as the first "killer app" of the crypto space, with annual on-chain transaction volume now exceeding $30 trillion — surpassing Visa and Mastercard combined. Yet most people, including many finance professionals, do not understand how they work, what distinguishes one type from another, or what risks they carry. This course, taught by Duke University Professor Campbell R. Harvey, provides a rigorous yet accessible foundation in stablecoin design, mechanics, and risk. You will learn how fiat-backed stablecoins like USDT and USDC maintain their peg, why tokenized gold could revive a voluntary gold standard, how crypto-collateralized systems like MakerDAO mirror central bank operations, and what caused the $40 billion Terra/Luna collapse. The course details a comprehensive risk taxonomy and an overview of emerging regulatory frameworks, including the GENIUS Act. It concludes that stablecoins will be the currency of the new world of AI-enabled agent-to-agent commerce. Whether you are a finance professional, policymaker, developer, or informed investor, this course equips you to evaluate stablecoins critically - understanding not just the opportunity, but the risks that come with a technology reshaping global payments.
Python and Rust with Linux Command Line Tools
Duke University (via Coursera)
This course is designed for beginners and those with some programming experience in either Python or Rust that want to implement automation and utilities in the command-line. Although no prior knowledge of Python or Rust is required, basic programming knowledge is recommended as well as some familiarity with the command-line interface (CLI). Throughout the course, you will gain a solid foundation for building efficient, reliable, and high-performance command-line tools that can help you automate tasks for data engineering, systems engineering, and DevOps. By completing this course, you will have the skills to develop and distribute sophisticated and efficient command-line tools.
Music as Biology: What We Like to Hear and Why
Duke University (via Coursera)
The course will explore the tone combinations that humans consider consonant or dissonant, the scales we use, and the emotions music elicits, all of which provide a rich set of data for exploring music and auditory aesthetics in a biological framework. Analyses of speech and musical databases are consistent with the idea that the chromatic scale (the set of tones used by humans to create music), consonance and dissonance, worldwide preferences for a few dozen scales from the billions that are possible, and the emotions elicited by music in different cultures all stem from the relative similarity of musical tonalities and the characteristics of voiced (tonal) speech. Like the phenomenology of visual perception, these aspects of auditory perception appear to have arisen from the need to contend with sensory stimuli that are inherently unable to specify their physical sources, leading to the evolution of a common strategy to deal with this fundamental challenge.
ART of the MOOC: Activism and Social Movements
Duke University (via Coursera)
This course is for activists, artists, and thinkers who wish to better understand and participate in social change. We will focus on the prolific and exciting overlap between socially engaged art and cultural practices generated by recent social movements around the world. Rather than assess the political efficacy of activities like mourning, listening, organizing, dancing, or partying, the lectures examine such cultural activities next to, and within, contemporary art practice. Included in the course are guest presentations by key artists, activists, and scholars, like: Rebecca Gomperts, Chido Govera, Gulf Labor, Hans Haacke, Sharon Hayes, Jolene Rickard, Gregory Sholette, Joshua Wong, and many more. Designed by artist and Duke professor, Pedro Lasch and co-taught by Creative Time artistic director, Nato Thompson, the course challenges learners to treat the MOOC itself as a social and artistic form. This happens mostly through the practical components, local project productions, global exchanges, and critical feedback. While no prior art making or activist experience is required, projects also offer challenging options for advanced learners. For other course offerings or language versions in this series, just search 'ART of the MOOC' inside the Coursera course catalogue.
Cash Flow Management
Duke University (via Coursera)
In this course, you will learn the importance of Return on Invested Capital (ROIC) and Free Cash Flow (FCF) as critical metrics for assessing a company’s financial health and investment attractiveness. Additionally, you will unpack the cash conversion cycle’s components to appreciate how effectively managing receivables, inventory, and payables can improve a company’s liquidity and operational efficiency. You will apply these concepts by performing financial analyses and completing practical assessments on cash flow management. This course is ideal for non-financial managers or professionals who seek to enhance their financial acumen to make better business decisions. No prior experience in finance is required. However, a basic understanding of business operations and strategic thinking will be beneficial.
Oil & Gas Industry Operations and Markets
Duke University (via Coursera)
The oil and gas industry has an enormous impact on all aspects of daily life. Individuals, corporations, and national governments make financial and policy decisions based on the cost, use, and availability of these two natural resources. This two-week course looks at the two most fundamental aspects of the oil and gas industry, its operations and markets, each of which is addressed as a separate module in the course. In the operations module, the course provides an overview of the production of oil and gas, from initial exploration to final transport. The second module focuses on the forces that drive the industry's operations, the oil and gas markets, including the cost of wells, seasonal impacts on prices, and the role of oil reserves. After every lesson, learners will take short quizzes to test their newly acquired knowledge, participant in crowd-sourced discussions about global markets, and complete a final project.
Copyright for Multimedia
Duke University (via Coursera)
Copyright questions about different formats (data, images, music and video) can be especially difficult. Sometimes the law specifically distinguishes between these different formats, and in most cases there are media-specific considerations that impact a copyright analysis. In this course we will look at four different media, paying special attention to the unique issues for each one and the kinds of information that is important when making copyright decisions for each type of material. We will work through fair use issues for each multimedia format, look at format-specific exceptions in the law, and consider unique issues for seeking permission for film, music, images and data. At the end of this course, participants will have a deeper understanding of how to apply our framework for making copyright decisions, and will be more comfortable with assessing multimedia issues. They will have gained more and more diverse experience for considering fair use.
Business Metrics for Data-Driven Companies
Duke University (via Coursera)
In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs. Finally, you will be able to use a checklist provided in the course to score any company on how effectively it is embracing big data culture. Digital companies like Amazon, Uber and Airbnb are transforming entire industries through their creative use of big data. You’ll understand why these companies are so disruptive and how they use data-analytics techniques to out-compete traditional companies.
Climate Science for Everyone
Duke University (via Coursera)
Climate change impacts everyone — from record-breaking heat waves, to physical and mental health impacts, to food shortages. Understanding the science behind climate change provides you with the foundational knowledge necessary for taking action in your community and enhancing your career. No matter your age, job, goals, or interests, this course will enable you to meaningfully engage with one of the defining challenges facing humanity today. What is the evidence for climate change? What key concepts describe the physical science of climate change? And are there ways to predict how the climate could change in the future? This short course provides everyone an entry-level overview of climate change science, with no science background needed! By the end of the course, you should be able to explain the causes of climate change and its impacts. Along the way, you’ll be given opportunities to consider how to apply this knowledge in your own life or career. Learning about climate science is the first step in your journey to becoming a more engaged global citizen as you help determine our planet’s future.
Linear Regression and Modeling
Duke University (via Coursera)
This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio.
Financing for Startup Businesses
Duke University (via Coursera)
This course will teach you how to manage a startup’s financing strategy, where you will learn how to build capitalization tables (or “cap tables”) in Excel. Cap tables will help you explore different financing strategies for your startup company and determine which financing decisions are best for your entrepreneurial venture. You will also learn about innovations in the digital space that allow new ways to finance entrepreneurial ventures. These include different forms of crowdfunding, and alternative credit scoring mechanisms based on web-based data. This course concludes with a module featuring cutting edge research from Duke University’s Fuqua School of Business on the financial technology industry. In this module, you will learn how financial technology companies are disrupting the credit scoring industry by developing new methods for credit scoring using consumers’ digital footprints. In addition, you will explore how financial technology platforms have introduced new, experimental forms of financing, such as crowdfunding.
Web Applications and Command-Line Tools for Data Engineering
Duke University (via Coursera)
In this fourth course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will build upon the data engineering concepts introduced in the first three courses to apply Python, Bash and SQL techniques in tackling real-world problems. First, we will dive deeper into leveraging Jupyter notebooks to create and deploy models for machine learning tasks. Then, we will explore how to use Python microservices to break up your data warehouse into small, portable solutions that can scale. Finally, you will build a powerful command-line tool to automate testing and quality control for publishing and sharing your tool with a data registry.
ART of the MOOC: Activismo y Movimientos Sociales
Duke University (via Coursera)
Este curso es para activistas, artistas y pensadores que deseen entender mejor el cambio social y participar en él. El contenido del curso enfoca en la coincidencia prolífica y emocionante entre el arte socialmente comprometido y prácticas culturales generadas por recientes movimientos sociales en todo el mundo. Más que evaluar la eficacia política de actividades como el luto, la escucha, la organización, el baile, o la fiesta, las conferencias examinan tales actividades culturales al lado y dentro de la práctica artística contemporánea. El curso incluye presentaciones de importantes artistas, activistas y académicos invitados como: Rebecca Gomperts, Chido GoVera, Gulf Labor, Hans Haacke, Sharon Hayes, Jolene Rickard, Gregory Sholette, Joshua Wong, y muchos más. Diseñado por el artista y profesor de Duke, Pedro Lasch, e impartido con el director artístico de Creative Time, Nato Thompson, este curso invita a todos los que participan en él a tratar el MOOC en sí mismo como una forma social y artística. Esto sucede sobre todo a través de los componentes prácticos, proyectos producidos localmente, intercambios mundiales, y el comentario crítico. No se requiere experiencia previa con el arte o el activismo, aunque los proyectos también incluyen buenas opciones para alumnos avanzados. Para otros cursos en esta serie o versiones en otros idiomas , solo busca 'ART of the MOOC' en el catálogo de Coursera
Managing Machine Learning Projects
Duke University (via Coursera)
This second course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the practical aspects of managing machine learning projects. The course walks through the keys steps of a ML project from how to identify good opportunities for ML through data collection, model building, deployment, and monitoring and maintenance of production systems. Participants will learn about the data science process and how to apply the process to organize ML efforts, as well as the key considerations and decisions in designing ML systems. At the conclusion of this course, you should be able to: 1) Identify opportunities to apply ML to solve problems for users 2) Apply the data science process to organize ML projects 3) Evaluate the key technology decisions to make in ML system design 4) Lead ML projects from ideation through production using best practices
Java Programming: Principles of Software Design
Duke University (via Coursera)
Solve real world problems with Java using multiple classes. Learn how to create programming solutions that scale using Java interfaces. Recognize that software engineering is more than writing code - it also involves logical thinking and design. By the end of this course you will have written a program that analyzes and sorts earthquake data, and developed a predictive text generator. After completing this course, you will be able to: 1. Use sorting appropriately in solving problems; 2. Develop classes that implement the Comparable interface; 3. Use timing data to analyze empirical performance; 4. Break problems into multiple classes, each with their own methods; 5. Determine if a class from the Java API can be used in solving a particular problem; 6. Implement programming solutions using multiple approaches and recognize tradeoffs; 7. Use object-oriented concepts including interfaces and abstract classes when developing programs; 8. Appropriately hide implementation decisions so they are not visible in public methods; and 9. Recognize the limitations of algorithms and Java programs in solving problems. 10. Recognize standard Java classes and idioms including exception-handling, static methods, java.net, and java.io packages.
Business Value Creation
Duke University (via Coursera)
In this course, you will learn how positive spread, healthy cash flows, meeting investor expectations, and sustaining competitive advantage are essential for creating long-term value in any organization. Additionally, you will understand the key factors that influence a company’s value, such as revenue growth, cost efficiency, asset utilization, and capital allocation. You will apply these concepts by analyzing real-world examples and completing practical assessments focused on value creation strategies. This course is ideal for non-financial managers or professionals who seek to enhance their financial acumen to make better business decisions. No prior experience in finance is required. However, a basic understanding of business operations and strategic thinking will be beneficial.
Data Science Ethics with R
Duke University (via Coursera)
Develop the ethical mindset every data scientist needs. In this course, you’ll examine the real-world implications of how data are collected, analyzed, and presented and the role of ethics in ensuring fairness, transparency, and trust. Through examples and case studies, you’ll learn to recognize misrepresentation in visualizations, algorithmic bias in models, and privacy risks in data collection. You’ll also explore strategies for mitigating these challenges and communicating results responsibly. By the end of this course, you’ll be able to identify ethical risks, apply frameworks for responsible data use, and make informed choices that uphold integrity in your analyses.
Startup Valuation Methods
Duke University (via Coursera)
How do different types of investors think about an investment opportunity? What kind of securities and contracts do they offer? How should a company decide what is a "good deal"? This course is designed to introduce you to the challenges and pitfalls of financing new enterprises. You will learn the basic tools for valuating companies, including using discounted cashflow analysis in Excel and understanding how to apply this model to your entrepreneurial venture. You will then learn how valuation works with different types of securities that investors use to finance startups, from bank loans to venture capital to angel investing.
Visual Perception and the Brain
Duke University (via Coursera)
Learners will be introduced to the problems that vision faces, using perception as a guide. The course will consider how what we see is generated by the visual system, what the central problem for vision is, and what visual perception indicates about how the brain works. The evidence will be drawn from neuroscience, psychology, the history of vision science and what philosophy has contributed. Although the discussions will be informed by visual system anatomy and physiology, the focus is on perception. We see the physical world in a strange way, and goal is to understand why.
Rust Secret Cipher CLI
Duke University (via Coursera)
In this guided project, we will build a command line application in Rust that can encrypt and decrypt text using a caesar cipher. The caesar cipher is a simple substitution cipher that shifts the letters of the alphabet by a set number of places. By the end of this guided project, you will be able to: Create a command line interface (CLI) application in Rust Implement caesar cipher encryption and decryption functions in Rust Build an executable binary that can encrypt/decrypt input text using caesar cipher Use Cargo for dependency and build management
Telehealth: Interprofessional Team-Based Care
Duke University (via Coursera)
How can you leverage your own telehealth skills to work with other health professionals as a team? What does your interprofessional health team need to provide your patients with efficient and effective virtual care? In this short course, we’ll build on telehealth essentials to discuss the basics of collaborating with others to form interprofessional telehealth teams. We’ll start by discussing the basics of team-based telehealth and how implementing these visits can benefit you and your patients. You’ll explore an example team-based visit and hear from providers who are implementing interprofessional telehealth models. By the end of the course, you’ll learn about necessary skills your team needs to develop: a team workflow, communication, and leveraging team members’ individual strengths. Learn how telehealth teams can solve issues related to limited physical clinic space and break down patient barriers to care. No matter what speciality or stage you’re at in your healthcare professional journey, this course will help you develop practical skills to be applied to your practice. No previous telehealth or specific technology experience is required.
برمجة Java: المصفوفات، والقوائم، والبيانات المصنفة
Duke University (via Coursera)
يمكنك الاعتماد على المهارات الهندسية للبرامج التي تعلمتها في "برمجة Java: حل المشكلات باستخدام البرامج" من خلال تعلم بني بيانات جديدة. استخدم بني البيانات هذه لإنشاء برامج أكثر تعقيدًا تستخدم خصائص Java الموجهة للكائن. في نهاية الدورة التدريبي، سيكون بإمكانك كتابة برنامج تشفير وبرنامج لكسر خوارزمية التشفير الخاصة بك. بعد الانتهاء من هذه الدورة التدريبي، سيكون بإمكانك: 1. قراءة البيانات وكتابتها من/إلى الملفات؛ 2. حل المشكلات المتعلقة بملفات البيانات؛ 3. إجراء تحليلات كمية للبيانات (على سبيل المثال، إيجاد الحدود القصوى والحدود الدنيا والمعدلات المتوسطة)؛ 4. تخزين البيانات ومعالجتها في مصفوفة أو Arraylist؛ 5. الجمع بين فئات متعددة لحل مشكلات أكبر؛ 6. استخدام العناصر التكرارية والمجموعات (بما في ذلك الخرائط) في Java.
Introduction to FastAPI framework
Duke University (via Coursera)
In this 2-hour hands-on course, you will build a web application with FastAPI. You will create routes to handle requests and responses, define request body models with validation, serve dynamic content, and run the API with Uvicorn. You will also leverage FastAPI's interactive OpenAPI docs to test endpoints and generate curl commands. By the end, you will have built and deployed a FastAPI web app using best practices for request handling, response validation, and documentation.
Programming Foundations with JavaScript, HTML and CSS
Duke University (via Coursera)
Learn foundational programming concepts (e.g., functions, for loops, conditional statements) and how to solve problems like a programmer. In addition, learn basic web development as you build web pages using HTML, CSS, JavaScript. By the end of the course, will create a web page where others can upload their images and apply image filters that you create. After completing this course, you will be able to: 1. Think critically about how to solve a problem using programming; 2. Write JavaScript programs using functions, for loops, and conditional statements; 3. Use HTML to construct a web page with paragraphs, divs, images, links, and lists; 4. Add styles to a web page with CSS IDs and classes; and 5. Make a web page interactive with JavaScript commands like alert, onClick, onChange, adding input features like an image canvas, button, and slider.
Data Science with NumPy, Sets, and Dictionaries
Duke University (via Coursera)
Become proficient in NumPy, a fundamental Python package crucial for careers in data science. This comprehensive course is tailored to novice programmers aspiring to become data scientists, software developers, data analysts, machine learning engineers, data engineers, or database administrators. Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like arrays, vectors, and matrices. Hands-on practice with NumPy will equip you with essential skills to tackle big data challenges and solve data problems effectively. You'll write Python programs to manipulate and filter data, as well as create useful insights out of large datasets. By the end of the course, you'll be adept at summarizing datasets, such as calculating averages, minimums, and maximums. Additionally, you'll gain advanced skills in optimizing data analysis with vectorization and randomizing data. Throughout your learning journey, you'll use many kinds of data structures and analytic techniques for a variety of data science challenges , including mathematical operations, text file analysis, and image processing. Stepwise, guided assignments each week will reinforce your skills, enabling you to solve problems and draw data-driven conclusions independently. Prepare yourself for a rewarding career in data science by mastering NumPy and honing your programming prowess. Start this transformative learning experience today!
Building a Bash Command-Line Tool
Duke University (via Coursera)
In this 2-hour long guided hands-on project, you will learn how to automate repetitive command line tasks with bash scripting. Through step-by-step video guidance, you will incrementally build a customized bash script for generating reports. First, you will learn bash scripting basics like variables, functions, and control flow. Next, you will handle command line arguments and add logic for different reporting options. By the end, you will have created your own reusable bash script ready to help increase your productivity! This project provides beginner-friendly bash scripting experience using real-world automating examples.
ART of the MOOC: Arte Público y Pedagogía
Duke University (via Coursera)
Los alumnos de este curso aprenderán a hacer sus propias obras de arte social y público si así lo desean, o podrán simplemente estudiar la teoría e historia reciente del medio. Diseñado por el artista y profesor de Duke, Pedro Lasch, e impartido con el director artístico de Creative Time, Nato Thompson, este curso presenta el arte y la cultura pública en sus formas contemporáneas radicalmente re-inventadas. Las conferencias enlazan acontecimientos claves de las últimas décadas en este campo con temas más amplios como la política espacial, estructuras sociales cotidianas y la educación experimental. También se incluyen presentaciones de importantes invitados especiales como: Tania Bruguera, Claire Doherty, Tom Finkelpearl, Hans Haacke, Shannon Jackson, Suzanne Lacy, Rick Lowe, y muchos más. Como implica el título del curso, “Arte del MOOC,” el proyecto invita a la comunidad entera de alumnos y participantes a tratar el MOOC en sí mismo como un medio de arte público. Esto sucede sobre todo a través de los componentes prácticos del curso, proyectos producidos localmente, intercambios globales, y los comentarios críticos. No se requiere experiencia previa con el arte o el activismo, aunque los proyectos también incluyen buenas opciones para alumnos avanzados. Para otros cursos en esta serie o versiones en otros idiomas , solo busca 'ART of the MOOC' en el catálogo de Coursera
Balance Sheet and Business Cases
Duke University (via Coursera)
In this course, you will delve into the income statement’s structure to uncover insights on revenue, expenses, and profitability, and how they reflect a company’s operational efficiency. Additionally, you will examine a balance sheet to understand a company’s financial stability, liquidity, and capital structure at a specific point in time. You will apply these concepts by conducting financial statement analyses and constructing compelling business cases. This course is ideal for non-financial managers or professionals who seek to enhance their financial acumen to make better business decisions. No prior experience in finance is required. However, a basic understanding of business operations and strategic thinking will be beneficial.
Interpretable Machine Learning
Duke University (via Coursera)
As Artificial Intelligence (AI) becomes integrated into high-risk domains like healthcare, finance, and criminal justice, it is critical that those responsible for building these systems think outside the black box and develop systems that are not only accurate, but also transparent and trustworthy. This course is a comprehensive, hands-on guide to Interpretable Machine Learning, empowering you to develop AI solutions that are aligned with responsible AI principles. You will also gain an understanding of the emerging field of Mechanistic Interpretability and its use in understanding large language models. Through discussions, case studies, programming labs, and real-world examples, you will gain the following skills: 1. Describe interpretable machine learning and differentiate between interpretability and explainability. 2. Explain and implement regression models in Python. 3. Demonstrate knowledge of generalized models in Python. 4. Explain and implement decision trees in Python. 5. Demonstrate knowledge of decision rules in Python. 6. Define and explain neural network interpretable model approaches, including prototype-based networks, monotonic networks, and Kolmogorov-Arnold networks. 7. Explain foundational Mechanistic Interpretability concepts, including features and circuits 8. Describe the Superposition Hypothesis 9. Define Representation Learning and be able to analyze current research on scaling Representation Learning to LLMs. This course is ideal for data scientists or machine learning engineers who have a firm grasp of machine learning but have had little exposure to interpretability concepts. By mastering Interpretable Machine Learning approaches, you'll be equipped to create AI solutions that are not only powerful but also ethical and trustworthy, solving critical challenges in domains like healthcare, finance, and criminal justice. To succeed in this course, you should have an intermediate understanding of machine learning concepts like supervis...
Emphasizing Christian Formation
Duke University (via Coursera)
Welcome to Emphasizing Christian Formation. This course examines how Methodism’s deep-rooted attention to Christian formation can nurture both gifts and character in our communities. We’ll see how Methodist formation hinges upon the Methodist doctrine of holiness. We’ll consider how innovations in the complementary practices of preaching and fellowship were directed to holiness and fueled the growth of Methodism in 18th-century England. We will also consider how education contributes to our growth as disciples of Christ. Drawing on these lessons allows us to rethink the practices of our own communities. Finally, we will learn that the Methodist way of Christian formation finds its fullest expression in prayer. Throughout four weeks, you will learn the definition of Christian formation— and how to connect this to your church and individual practices and forming diverse communities of faith. In each week of the course, you’ll be asked to reflect on scripture to guide you to take practical steps in how to incorporate theology in your own worship, fellowship, teaching, and mission. If you are a pastor or ministry professional in need of Continuing Education Unit (CEU) credits for your professional development, CEU credits are available for this course. Upon successful completion of this course, you can provide your Coursera certificate and the course description to your employer for recognition of earning 0.5 CEUs. Contact divinityonline@duke.edu with any questions regarding CEUs for this course. Each of the 5 courses in the Rediscovering the Heart of Methodism specialization is worth 0.5 CEUs, for a total of 2.5 CEUs for completing all of the courses. This course is part of the Rediscovering the Heart of Methodism series. This is one of five 4-week online courses designed to help engaged laypeople and clergy (including local pastors in licensing schools) develop core capacities for innovative leadership within the Wesleyan tradition. Through this series, we hope ...
Writing, Running, and Fixing Code in C
Duke University (via Coursera)
Building on the course Programming Fundamentals, this course will teach you how to write code by first planning what your program should do—an important approach for novice and professional programmers. You will learn how to compile and run your program, and then how to test and debug it. This course builds on the Seven Steps you have already learned and provides a framework for systematically testing for problems and fixing them, so you can find and fix problems efficiently.
Financial Statements
Duke University (via Coursera)
In this course, you will gain insights into how analyzing income statements, balance sheets, and cash flow statements can provide a comprehensive understanding of a company’s financial performance and condition. You will apply these concepts by conducting detailed financial statement analyses and interpreting the results to make informed business decisions. This course is ideal for non-financial managers or professionals who seek to enhance their financial acumen to make better business decisions. No prior experience in finance is required. However, a basic understanding of business operations and strategic thinking will be beneficial.
Impact Measurement & Management for the SDGs
Duke University (via Coursera)
How can businesses and investors help fill the multi-trillion-dollar gap needed for sustainable development? Simply put: by incorporating sustainability and social impact factors on people and planet into management decisions. Through this course, anyone can learn to improve their organization's practice of impact measurement and management and align their ESG or impact activities and reporting with emerging global standards. Impact Measurement and Management for the SDGs is a collaboration between UNDP SDG Impact and the award-winning team at CASE at Duke University. The United Nations Development Programme (UNDP) is a steward of the United Nations Sustainable Development Goals (SDGs) that were launched in 2015 and to which 193 countries have signed up to achieve by 2030. The SDGs are a shared plan to end extreme poverty, reduce inequality, and protect the planet; they have become the world’s blueprint to achieve a better and more sustainable future for all. But the public sector cannot meet those goals alone. Climate change, poverty, racial and gender equity, food, health, education, clean water − the list of challenges faced by people and planet is too long. Businesses and investors have stepped in to help. The course was designed around the fundamental elements of the SDG Impact Standards, the only management standards that embed sustainability at the core of an organization in the holistic way intended by the creators of the SDGs. The course demonstrates how the SDG Impact Standards help organizations align with responsible business principles, other standards, and best practices in impact management. In the course, you’ll learn to improve decision-making for positive impact on people and planet in line with the SDG Impact Standards and the Operating Principles for Impact Management. In the course, we have translated 4 universal practices of impact management into practical actions: SET STRATEGY, INTEGRATE, OPTIMIZE and REINFORCE. We teach the steps to i...
Agile Strategy for Competitive Advantage
Duke University (via Coursera)
In this course, you will learn how to identify and capitalize on transient sources of competitive advantage in today’s fast-paced business environment. You will understand the shift from traditional, sustainable advantages to more dynamic, flexible ones that require agility in decision-making and strategy. Additionally, you will explore how modern leaders can navigate disruptions and leverage innovation to stay ahead of competitors. Real-world examples and practical assessments will help you apply these concepts to your business context. This course is ideal for managers and business leaders who seek to enhance their strategic thinking and adapt to market changes. A basic understanding of business operations will be helpful, but no prior experience in agility or strategy is required.
Behavioral Finance
Duke University (via Coursera)
We make thousands of decisions every day. Do I cross the road now, or wait for the oncoming truck to pass? Should I eat fries or a salad for lunch? How much should I tip the cab driver? We usually make these decisions with almost no thought, using what psychologists call “heuristics” – rules of thumb that enable us to navigate our lives. Without these mental shortcuts, we would be paralyzed by the multitude of daily choices. But in certain circumstances, these shortcuts lead to predictable errors – predictable, that is, if we know what to watch out for. Did you know, for example, that we are naturally biased towards selling investments that are doing well for us, but holding on to those that are doing poorly? Or that we often select sub-optimal insurance payment plans, and routinely purchase insurance that we don’t even need? And why do so many of us fail to enroll in our employer’s corporate retirement plans, even when the employer offers to match our contributions? Behavioral finance is the study of these and dozens of other financial decision-making errors that can be avoided, if we are familiar with the biases that cause them. In this course, we examine these predictable errors, and discover where we are most susceptible to them. This course is intended to guide participants towards better financial choices. Learn how to improve your spending, saving, and investing decisions for the future.
Data Visualization and Modeling in Python
Duke University (via Coursera)
Put the keystone in your Python Data Science skills by becoming proficient with Data Visualization and Modeling. This course is suited for intermediate programmers, who have some experience with NumPy and Pandas, that want to expand their skills for any career in data science. Whether you come to data science through social sciences and Statistics, or from a programming background, this course will integrate the two perspectives and offer unique insights from each. You’ll begin by becoming adept with matplotlib, an essential plotting library in Python that will enable you to discover and communicate insights about data effectively. You’ll progress to classification algorithms by creating a K-Nearest Neighbors (KNN) classifier, a foundational algorithm used in data science and machine learning. Finally, you will write Python programs that leverage your newfound data science skills based on inferential statistics, and be able to describe relationships between variables in your data. By the end of the course, you’ll be able to quickly visualize a dataset, explore it for insights, determine relationships between data, and communicate it all with effective plots. In the last module of this course, you’ll produce a publication-quality figure based on data that you’ve prepared and cleaned yourself; the first artifact in your data science portfolio. Throughout this course you’ll get plenty of hands-on experience through interactive programming assignments, live coding demos from data scientists, and analyzing the data behind important real-world problems (like carbon emissions, real estate prices, and infant mortality). Guided activities throughout each module will reinforce your proficiency with data science techniques and analytical approach as a data scientist. Solidify your understanding of these critical data science concepts and begin your data science portfolio by mastering visualization and modeling. Start this integrative and transformative learning journey tod...
Decentralized Finance (DeFi) Deep Dive
Duke University (via Coursera)
DeFi and the Future of Finance is a set of four courses that focus on decentralized finance. The third course is called DeFi Deep Dive. It is essential that you do the first two courses I. DeFi Infrastructure and II. DeFi Primitives before doing this course. It is the longest of the four courses and focuses on some of the leading protocols in the DeFi space. We will look at Credit and Lending (and feature MakerDAO, Compound and Aave), Decentralized Exchange with an analysis of how protocols like Uniswap and Balancer works, Derivatives (featuring Yield Protocol, dYdX and Synthetix) and Tokenization with an analysis of Set Protocol as well as wrapped bitcoin. For many of these leading protocols, we include detailed examples of how the mechanics work. For example, we show how to use a dYdX flash swap to execute an arbitrage transaction (take advantage of different prices on different exchanges for the same asset).
Cultivating a Scriptural Imagination
Duke University (via Coursera)
What does it mean to have a scriptural imagination, and how do we develop this kind of imagination in Christian community? How can a scriptural imagination help us become more active participants in God’s unfolding story of redemption? This Duke Divinity+ course explores the common values and scriptural framework that is at the heart of Methodism. Throughout four weeks, you will learn the definition of scriptural imagination — and how to connect this to your church and individual practices and forming diverse communities of faith. In each week of the course, you’ll be asked to reflect on scripture to guide you to take practical steps in how to incorporate theology in your own worship, fellowship, teaching, and mission. This course is part of the Rediscovering the Heart of Methodism series. This is one of five 4-week online courses designed to help engaged laypeople and clergy (including local pastors in licensing schools) develop core capacities for innovative leadership within the Wesleyan tradition. If you are a pastor or ministry professional in need of Continuing Education Unit (CEU) credits for your professional development, CEU credits are available for this course. Upon successful completion of this course, you can provide your Coursera certificate and the course description to your employer for recognition of earning 0.5 CEUs. Contact divinityonline@duke.edu with any questions regarding CEUs for this course. Each of the 5 courses in the Rediscovering the Heart of Methodism specialization is worth 0.5 CEUs, for a total of 2.5 CEUs for completing all of the courses. Through this series, we hope you will experience a deeper grounding in the distinctive elements of Methodism at its best, and a renewed capacity for hopeful, imaginative participation in the mission of God.
Agile Decision-Making Frameworks
Duke University (via Coursera)
In this course, you will learn how to make strategic decisions quickly and effectively in uncertain and complex environments. You will explore frameworks and tools that enable faster decision-making while maintaining accuracy and confidence. This module will also cover the balance between speed and thoroughness, helping you make high-quality decisions without sacrificing agility. This course is suited for professionals and leaders who need to enhance their decision-making skills to adapt to fast-moving environments. No prior knowledge of decision frameworks is necessary.
Java Programming: Solving Problems with Software
Duke University (via Coursera)
Learn to code in Java and improve your programming and problem-solving skills. You will learn to design algorithms as well as develop and debug programs. Using custom open-source classes, you will write programs that access and transform images, websites, and other types of data. At the end of the course you will build a program that determines the popularity of different baby names in the US over time by analyzing comma separated value (CSV) files. After completing this course you will be able to: 1. Edit, compile, and run a Java program; 2. Use conditionals and loops in a Java program; 3. Use Java API documentation in writing programs. 4. Debug a Java program using the scientific method; 5. Write a Java method to solve a specific problem; 6. Develop a set of test cases as part of developing a program; 7. Create a class with multiple methods that work together to solve a problem; and 8. Use divide-and-conquer design techniques for a program that uses multiple methods.
Telehealth: Neurologic Assessment
Duke University (via Coursera)
How can telehealth visits increase patient access to neurologic health care? How can you successfully guide patients and their caregivers through a telehealth visit? In this short course, we’ll discuss the benefits and constraints of virtual neurological visits as well as practical strategies to make these visits successful for both you and your patients. Building on your clinical knowledge, we give helpful ways to modify your practice to suit the context of a telehealth video visit. This course will discuss when it is appropriate to complete a neurological assessment versus when patients should be seen in-person. We’ll discuss how caregivers and assistants play a key role in successful visits and patient safety and how to evaluate pediatric and cognitively impaired patients. No matter if you’re an experienced healthcare professional or a healthcare student interested in neurology, this course introduces you to the basics of virtual physical assessments. By taking this course, you can contribute to broadening patient access to neurological healthcare. This course doesn’t assume any previous experience with telehealth or specific technologies, but will rely on your previous experience with physical assessments. Whether you are extremely adept at performing telehealth visits, or a complete novice, this course contains practices and expert guidance to positively benefit your telehealth practice.
Virtualization, Docker, and Kubernetes for Data Engineering
Duke University (via Coursera)
Throughout this course, you'll explore virtualization, containerization, and Kubernetes, mastering the very tools that power data engineering in the industry. Each week presents a new set of tools and platforms that are indispensable in data engineering. From mastering Docker and Kubernetes to exploring advanced topics such as AI-driven coding with GitHub Copilot, efficient container image management with Azure and Amazon Elastic Container Registries, and Site Reliability Engineering (SRE) practices, you'll go beyond the basics and acquire the expertise needed to thrive in the dynamic and data-driven landscape of advanced data engineering. Whether you're a current student looking to expand your skills or a working professional aiming to take your expertise to the next level, this course is tailored to equip you with the advanced knowledge and hands-on experience necessary for success.
Risk Management and Financial Theory
Duke University (via Coursera)
In this course, you will explore various types of financial risks, including market, credit, and operational risks, and learn strategies for managing and mitigating them. Additionally, you will master the art of building compelling business cases, focusing on strategic alignment, financial justification, risk assessment, and stakeholder communication. You will also understand the fundamental principle that money available now is worth more than the same amount in the future due to its potential earning capacity. You will apply these concepts through scenario-based assessments and financial theory exercises. This course is ideal for non-financial managers or professionals who seek to enhance their financial acumen to make better business decisions. No prior experience in finance is required. However, a basic understanding of business operations and strategic thinking will be beneficial.
Tropical Parasitology: Protozoans, Worms, Vectors and Human Diseases
Duke University (via Coursera)
This course provides students an understanding of important human parasitic diseases, including their life cycles, vectors of transmission, distribution and epidemiology, pathophysiology and clinical manifestations, treatment, and prevention and control. Tropical Parasitology is taught by faculty from an area highly impacted by tropical parasites- the Kilimanjaro Christian Medical University College in Moshi, Tanzania. The faculty include Drs. Frank Mosha and Mramba Nyindo (and two lecturers, Drs. Johnson Matowo and Jovin Kitau). Dr. John Bartlett, Professor of Medicine, Global Health and Nursing at Duke University, joins his faculty colleagues in this effort.
Introduction to Chemistry: Structures and Solutions
Duke University (via Coursera)
This is an introductory course for students with limited background in chemistry; basic concepts such as atomic and molecular structure, solutions, phases of matter, and quantitative problem solving will be emphasized with the goal of preparing students for further study in chemistry.
Advanced Data Engineering
Duke University (via Coursera)
In this advanced course, you will gain practical expertise in scaling data engineering systems using cutting-edge tools and techniques. This course is designed for data scientists, data engineers, and anyone with a foundational understanding of data handling who desires to escalate their skills to handle larger, more complex datasets efficiently. Throughout the course, you'll master the application of technologies such as Celery with RabbitMQ for scalable data consumption, Apache Airflow for optimized workflow management, and Vector and Graph databases for robust data management at scale. The course will culminate with hands-on projects that offer real-world experience, where you'll put your acquired skills to test in solving data engineering challenges. You will not only learn to create scalable data systems but also to analyze their performance and make necessary adjustments for optimum results. This invaluable experience in advanced data engineering techniques will prepare you for the demanding tasks of handling massive datasets, streamlining complex workflows, and optimizing data operations for businesses of any scale.
Data Visualization with Python
Duke University (via Coursera)
In today's data-driven world, the ability to create compelling visualizations and tell impactful stories with data is a crucial skill. This comprehensive course will guide you through the process of visualization using coding tools with Python, spreadsheets, and BI (Business Intelligence) tooling. Whether you are a data analyst, a business professional, or an aspiring data storyteller, this course will provide you with the knowledge and best practices to excel in the art of visual storytelling. Throughout the course, a consistent dataset will be used for exercises, enabling you to focus on mastering the visualization tools rather than getting caught up in the intricacies of the data. The emphasis is on practical application, allowing you to learn and practice the tools in a real-world context. To fully leverage the Python sections of this course, prior experience programming in Python is recommended. Additionally, a solid understanding of high-school level math is expected. Familiarity with the Pandas library will also be beneficial. By the end of this course, you will possess the necessary skills to become a proficient data storyteller and visual communicator. With the ability to create compelling visualizations and leverage the appropriate tools, you will be well-equipped to navigate the world of data and make informed decisions that drive meaningful impact.
Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital
Duke University (via Coursera)
In this course, you will learn the science behind how digital images and video are made, altered, stored, and used. We will look at the vast world of digital imaging, from how computers and digital cameras form images to how digital special effects are used in Hollywood movies to how the Mars Rover was able to send photographs across millions of miles of space. The course starts by looking at how the human visual system works and then teaches you about the engineering, mathematics, and computer science that makes digital images work. You will learn the basic algorithms used for adjusting images, explore JPEG and MPEG standards for encoding and compressing video images, and go on to learn about image segmentation, noise removal and filtering. Finally, we will end with image processing techniques used in medicine. This course consists of 7 basic modules and 2 bonus (non-graded) modules. There are optional MATLAB exercises; learners will have access to MATLAB Online for the course duration. Each module is independent, so you can follow your interests.
The Brain and Space
Duke University (via Coursera)
This course is about how the brain creates our sense of spatial location from a variety of sensory and motor sources, and how this spatial sense in turn shapes our cognitive abilities. Knowing where things are is effortless. But “under the hood,” your brain must figure out even the simplest of details about the world around you and your position in it. Recognizing your mother, finding your phone, going to the grocery store, playing the banjo – these require careful sleuthing and coordination across different sensory and motor domains. This course traces the brain’s detective work to create this sense of space and argues that the brain’s spatial focus permeates our cognitive abilities, affecting the way we think and remember. The material in this course is based on a book I've written for a general audience. The book is called "Making Space: How the Brain Knows Where Things Are", and is available from Amazon, Barnes and Noble, or directly from Harvard University Press. The course material overlaps with classes on perception or systems neuroscience, and can be taken either before or after such classes. Dr. Jennifer M. Groh, Ph.D. Professor Psychology & Neuroscience; Neurobiology Duke University www.duke.edu/~jmgroh Jennifer M. Groh is interested in how the brain process spatial information in different sensory systems, and how the brain's spatial codes influence other aspects of cognition. She is the author of a recent book entitled "Making Space: How the Brain Knows Where Things Are" (Harvard University Press, fall 2014). Much of her research concerns differences in how the visual and auditory systems encode location, and how vision influences hearing. Her laboratory has demonstrated that neurons in auditory brain regions are sometimes responsive not just to what we hear but also to what direction we are looking and what visual stimuli we can see. These surprising findings challenge the prevailing assumption that the brain’s sensory pathways remain se...
MLOps Tools: MLflow and Hugging Face
Duke University (via Coursera)
This course covers two of the most popular open source platforms for MLOps (Machine Learning Operations): MLflow and Hugging Face. We’ll go through the foundations on what it takes to get started in these platforms with basic model and dataset operations. You will start with MLflow using projects and models with its powerful tracking system and you will learn how to interact with these registered models from MLflow with full lifecycle examples. Then, you will explore Hugging Face repositories so that you can store datasets, models, and create live interactive demos. By the end of the course, you will be able to apply MLOps concepts like fine-tuning and deploying containerized models to the Cloud. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their programming skills.
Advertising and Society
Duke University (via Coursera)
This course examines the relation of advertising to society, culture, history, and the economy. Using contemporary theories about visual communications, we learn to analyze the complex levels of meaning in both print advertisements and television commercials. About the Course The course covers a wide range of topics, including the origins of advertising, the creation of ads, the interpretation of ads, the depiction of race, class, gender, and sexuality in advertising, sex and selling, adverting and ethics, and the future of advertising. The lectures will discuss theoretical frameworks and apply them to specific advertisements. Course Syllabus Week 1: What is advertising and where did it come from? Week 2: Am I being manipulated by advertising? Week 3: What’s in an ad beyond that which meets the eye? Week 4: How do ads get made? Week 5: What do ads teach us about race, class, gender, and sexuality? Week 6: Does sex sell? Week 7: What is the future of advertising? Recommended Background No background is required; everyone is welcome! Suggested Readings Although the lectures are designed to be self-contained, we recommend that students refer to the free online textbook ADTextOnline.org. Other free resources will be suggested for each week’s module. Course Format Most videos will be lectures with instructor talking. Each lecture will be illustrated with PowerPoint slides, print advertisements, and TV commercials. The videos for each week will consist of segments that add up to about an hour. Each week will have one quiz that will appear as stand-alone homework. All resources beyond lectures will be available online to students at no charge. Most of these will be from ADTextOnline.org. Others will be visits to the sites of ad agencies in the US and abroad, open access websites that deal with course topics, and open-access journal articles.
Rust for DevOps
Duke University (via Coursera)
Rust For DevOps is an intermediate level course for software engineers, system administrators, and technical professionals looking to apply DevOps principles using Rust. This course is for you if you have beginner level programming experience and are familiar with Linux, Git, and Docker fundamentals. Through video lessons and coding exercises, you will gain practical Rust skills to build, deploy, and monitor applications using DevOps workflows. You will implement containerization, instrument your code for observability, and automate common administration tasks like file parsing and cron jobs. By the end, you will have the Rust and DevOps skills to rapidly develop robust large-scale applications, regardless of your specific technical role.
Decentralized Finance (DeFi) Opportunities and Risks
Duke University (via Coursera)
DeFi and the Future of Finance is a set of four courses that focus on decentralized finance. The final course is called DeFi Opportunities and Risks. It is essential that you complete the first three courses: I. DeFi Infrastructure; II. DeFi Primitives; and III. DeFi Deep Dive before beginning the fourth course. The course starts with the premise that an analysis of any new technology must clearly gauge the risks and challenges. Given that DeFi is only a few years old there are plenty of risks. The course begins with the most obvious risk: smart contract risk. Smart contracts are foundational for DeFi. The code of these contracts is public - opening a clear attack vector for hackers. That is, in traditional finance, hackers need to break into a system to get access to the code and data. In DeFi, everything is open source.There are many other risks studied including: Governance risk; Oracle risk; Scaling risk; Decentralized Exchange or DEX risk; Custodial risk; Environmental risk; and Regulatory risk.
Agile Team Leadership
Duke University (via Coursera)
In this course, you will learn how to build and lead agile teams that can quickly respond to changing market conditions and drive innovation. You will explore the principles of agile team dynamics, collaboration, and empowerment, and how to create an environment where teams can operate autonomously while maintaining alignment with broader organizational goals. This course is perfect for team leaders and managers seeking to improve team agility and collaboration. A background in team leadership will be beneficial but is not required.
Human Factors in AI
Duke University (via Coursera)
This third and final course of the AI Product Management Specialization by Duke University's Pratt School of Engineering focuses on the critical human factors in developing AI-based products. The course begins with an introduction to human-centered design and the unique elements of user experience design for AI products. Participants will then learn about the role of data privacy in AI systems, the challenges of designing ethical AI, and approaches to identify sources of bias and mitigate fairness issues. The course concludes with a comparison of human intelligence and artificial intelligence, and a discussion of the ways that AI can be used to both automate as well as assist human decision-making. At the conclusion of this course, you should be able to: 1) Identify and mitigate privacy and ethical risks in AI projects 2) Apply human-centered design practices to design successful AI product experiences 3) Build AI systems that augment human intelligence and inspire model trust in users
Introduction to Chemistry: Reactions and Ratios
Duke University (via Coursera)
This is an introductory course for students with limited background in chemistry; basic concepts involved in chemical reactions, stoichiometry, the periodic table, periodic trends, nomenclature, and chemical problem solving will be emphasized with the goal of preparing students for further study in chemistry as needed for many science, health, and policy professions.
Dog Emotion and Cognition
Duke University (via Coursera)
Dog Emotion and Cognition will introduce you to the exciting new study of dog psychology, what the latest discoveries tell us about how dogs think and feel about us, and how we can use this new knowledge to further strengthen our relationship with our best friends.
Telehealth: Dermatology Assessment
Duke University (via Coursera)
Dermatological assessments require precise focus, lighting, and clear demarcation of affected areas, but how can you achieve these results via telehealth? What tools are available to remote patients for taking high quality images, and how can you as a healthcare provider leverage everyday items to improve patient care outcomes? From photography basics to using specialized clinical photography equipment, we cover the essentials for providing high quality remote care to patients with dermatological concerns. This course walks you through the process of obtaining clinically useful imagery after the reporting of a dermatological complaint. We’ll model advice you can give to patients or caregivers, tips for working with everyday technology to take clinically useful images, and common pitfalls in teledermatology. To bring it all together, we’ll also provide advice on how to leverage more specialized devices, like portable dermatoscopes, to provide high-resolution images that can more accurately identify skin conditions and patient status. This course doesn’t assume any previous experience with telehealth or specific technologies but will rely on your previous experience with physical assessments. Whether you are extremely adept at performing telehealth visits or a novice, this course contains practices and expert guidance to positively benefit your practice.
ESG Communication for Inclusive Dialogue
Duke University (via Coursera)
This course invites participants to explore the emotive and often contentious nature of Environmental, Social, and Governance (ESG) topics, offering tools to foster meaningful dialogue. Learners will examine personal and societal biases, develop skills for inclusive, non-judgmental conversations, and explore the concept of climate justice. Designed for anyone seeking to build awareness and communication skills, this course emphasizes making ESG an inclusive, shared responsibility and promoting constructive engagement across diverse perspectives.
Electric Industry Operations and Markets
Duke University (via Coursera)
This is a two week course. In the first week you will learn about the core activities that the Industry executes to bring electricity to customers. We will review what electricity is, how it is generated, how it is transmitted, how it comes into buildings, and how consumption of electricity instantly feeds back on the transmission and generation of electricity. You will learn to: Define what electricity is; Describe how electricity is generated, transmitted and distributed; Describe how electricity is generated, transmitted and distributed; and Summarize how the consumption of electric energy instantly feeds back on the transmission and generation of electricity. In the second week, the course shifts to the markets that drive Electric Industry operations. You will learn about the various costs of the electric industry’s core activities, how electricity is priced, the various ways that electric markets are structured, how these market structures determine which power plants are dispatched to produce electricity when, and how recent changes in generator fuel prices, generation technology, market regulations, and environmental regulations are transforming both Electric Industry Markets and Operations. You will learn to: Describe the main cost components to the electric system; Compare the costs of different types of power plants; Interpret the retail pricing of electricity; Explain the different types of electric markets and understand how they operate to dispatch electric supply to meet demand in real time; and Explain why and how the electric industry is regulated.
Data Visualization and Communication with Tableau
Duke University (via Coursera)
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses. By the end, you will know how to structure your data analysis projects to ensure the fruits of your hard labor yield results for your stakeholders. You will also know how to streamline your analyses and highlight their implications efficiently using visualizations in Tableau, the most popular visualization program in the business world. Using other Tableau features, you will be able to make effective visualizations that harness the human brain’s innate perceptual and cognitive tendencies to convey conclusions directly and clearly. Finally, you will be practiced in designing and persuasively presenting business “data stories” that use these visualizations, capitalizing on business-tested methods and design principles.
Python and Pandas for Data Engineering
Duke University (via Coursera)
In this first course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will learn how to set up a version-controlled Python working environment which can utilize third party libraries. You will learn to use Python and the powerful Pandas library for data analysis and manipulation. Additionally, you will also be introduced to Vim and Visual Studio Code, two popular tools for writing software. This course is valuable for beginning and intermediate students in order to begin transforming and manipulating data as a data engineer.
Cloud Machine Learning Engineering and MLOps
Duke University (via Coursera)
Welcome to the fourth course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will build upon the Cloud computing and data engineering concepts introduced in the first three courses to apply Machine Learning Engineering to real-world projects. First, you will develop Machine Learning Engineering applications and use software development best practices to create Machine Learning Engineering applications. Then, you will learn to use AutoML to solve problems more efficiently than traditional machine learning approaches alone. Finally, you will dive into emerging topics in Machine Learning including MLOps, Edge Machine Learning and AI APIs. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a Flask web application that serves out Machine Learning predictions.
Cloud Data Engineering
Duke University (via Coursera)
Welcome to the third course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn how to apply Data Engineering to real-world projects using the Cloud computing concepts introduced in the first two courses of this series. By the end of this course, you will be able to develop Data Engineering applications and use software development best practices to create data engineering applications. These will include continuous deployment, code quality tools, logging, instrumentation and monitoring. Finally, you will use Cloud-native technologies to tackle complex data engineering solutions. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you will build a serverless data engineering pipeline in a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP).
Data Engineering with Rust
Duke University (via Coursera)
Are you a data engineer, software developer, or a tech enthusiast with a basic understanding of Rust, seeking to enhance your skills and dive deep into the realm of data engineering with Rust? Or are you a professional from another programming language background, aiming to explore the efficiency, safety, and concurrency features of Rust for data engineering tasks? If so, this course is designed for you. While a fundamental knowledge of Rust is expected, you should ideally be comfortable with the basics of data structures and algorithms, and have a working understanding of databases and data processing. Familiarity with SQL, the command line, and version control with git is advantageous. This four-week course focuses on leveraging Rust to create efficient, safe, and concurrent data processing systems. The journey begins with a deep dive into Rust's data structures and collections, followed by exploring Rust's safety and security features in the context of data engineering. In the subsequent week, you'll explore libraries and tools specific to data engineering like Diesel, async, Polars, and Apache Arrow, and learn to interface with data processing systems, REST, gRPC protocols, and AWS SDK for cloud-based data operations. The final week focuses on designing and implementing full-fledged data processing systems using Rust. By the end of this course, you will be well-equipped to use Rust for handling large-scale data engineering tasks, solving real-world problems with efficiency and speed. The hands-on labs and projects throughout this course will ensure you gain practical experience, putting your knowledge into action. This course is your gateway to mastering data engineering with Rust, preparing you for the next level in your data engineering journey.
Python Generators
Duke University (via Coursera)
In this 1-hour hands-on project, you will learn how to build and utilize generator functions for efficient lazy sequence generation in Python. Specifically, you will understand how to: Define generator functions using yield statements to lazily produce values Create infinite data streams with recurrent generators Apply generators for data processing pipelines and transformations Use generator expressions for inline lazy object creation
Introduction to GitHub Actions
Duke University (via Coursera)
GitHub Actions allows you to automate your software development workflows and seamlessly integrate with GitHub. This 2-hour long project will guide you through the fundamentals of GitHub Actions, helping you leverage its automation capabilities for your projects. We’ll start by overviewing the core components of Actions including workflow files, jobs, steps, and runners. You’ll learn how to monitor and trigger workflows based on events like pushing code. We’ll walk through creating a simple starter workflow YAML file that clones a repository, sets up a language, and builds an application. To apply what you've learned, you’ll create and customize a workflow for your own project using reusable open source actions from GitHub Marketplace. Whether you're new to GitHub Actions or looking to expand your skills, this project will equip you with the knowledge and hands-on practice to implement automation best practices. You’ll gain practical experience configuring Actions for continuous integration, deployment, and other tasks to boost your productivity.
Church Administration Foundations
Duke University (via Coursera)
Why is effective church administration essential for healthy Christian ministries? What role does time management and delegation play in effective church leadership? In this short course for church pastors and lay leaders, you will engage church admin as a set of practices that support effective discipleship, formation, witness, and worship. You will assess your current ability to demonstrate church admin competencies and learn practical tips in time management and delegation for how you can grow as a theologically grounded administrator. You will also hear guest lectures about elements of pastoral leadership, highlighting why values and cultural humility transform your church admin into discipleship. This foundational course is a preview of Duke University's Church Administration four-course series, offered by Duke Divinity+ . Dr. Rae Cho teaches course 1, Church Administration Theology and Time Management and course 2, Strategic Management for Churches. Dr. Russ Elmayan teaches course 3, Human Resource Stewardship for Churches, and course 4, Financial Management for Churches.
FinTech Law and Policy
Duke University (via Coursera)
Being a successful FinTech firm requires more than just great technology; it also requires an understanding of the laws and regulations applicable to your business. This course will provide you with that understanding. You will learn about the critical legal, regulatory, and policy issues associated with cryptocurrencies, initial coin offerings, online lending, new payments and wealth management technologies, and financial account aggregators. In addition, you will learn how regulatory agencies in the U.S. are continually adjusting to the emergence of new financial technologies and how one specific agency has proposed a path for FinTech firms to become regulated banks. You will also learn the basics of how banks are regulated in the U.S. If you are unfamiliar with how these new financial technologies work, fear not. We will begin each new course section with a high-level overview of the underlying technology. While the course is principally focused on the U.S. FinTech industry, we cannot possibly cover every relevant legal and regulatory issue. Therefore, this course should not be construed as legal advice. Rather, the goal of the course is to familiarize you with the key legal and regulatory challenges FinTech firms in various sectors face, as well as the critical policy debates that are occurring in Washington D.C. and state capitals across the country.
Community-Based Climate Change Solutions
Duke University (via Coursera)
Climate change will have tremendous impacts on every human community across the globe. However, because of the context of both how climate is changing and how communities are organized and function, it can be disastrous to apply the same solutions across the board. This course will teach you the basic principles needed to identify the dynamics and needs of each community, build on its strengths, and adopt best practices and practical frameworks for adapting climate change solutions to local contexts. You’ll learn tools and approaches to put these principles into practice across different community settings, regardless of your level of prior experience. This course is intended for professionals who have been tasked with implementing climate change solutions at the community level, whether in urban or rural areas or in industrialized or developing countries. Upon completion of the course, you will be able to effectively select and adapt climate change solutions to best match the specific social and environmental context of each community, and to engage community members in implementing sustainable solutions that produce positive, equitable outcomes. This course requires no previous knowledge of climate change solutions or of community engagement, and people with this knowledge will also benefit from the course.
Christian Virtues for Spiritual Growth
Duke University (via Coursera)
This Duke Divinity+ course is for all those who seek to cultivate their interior lives and to develop a way of thinking about ethics inspired by Christian tradition. In this course, renowned theologian Stanley Hauerwas reflects on the significance of specific virtues for understanding what it means to be a Christian. He examines the meaning and significance of four key virtues—kindness, hope, humility, and generosity—and their importance to living a good life. Further, you will consider the practical aspects of living a virtuous life. We will discuss the challenges to living the virtues, and examine how they can be cultivated by incorporating contemplative practices in your everyday life. Week 1 draws on baptism as our initiation into a new story and way of being in the world. In Week 1, you will explore the virtue of kindness through the character of God, reflected in how we treat ourselves and others. Week 2 focuses on hope. In Week 3, you will explore the virtue of humility, and reflecting on the paradox that trying to be humble often ends in pride. Finally, Week 4 closes with an exploration of generosity, demonstrating how different virtues reveal the God who is unrelentingly generous.
ESG Challenges and Solutions for Business
Duke University (via Coursera)
This course tackles the barriers and challenges that hinder the adoption of Environmental, Social, and Governance (ESG) practices. Learners will explore organizational roadblocks, personal hesitations, and key issues related to ethics, compliance, and regulations. Through practical strategies and insights, participants will develop the skills to overcome these challenges, foster a culture of accountability, and implement sustainable, ethical practices within their organizations and beyond.
Telehealth: Cardiopulmonary Assessment
Duke University (via Coursera)
How can you reliably provide cardiopulmonary care for patients virtually? What types of remote monitoring devices can you use to diagnose cardiopulmonary complaints? What cardiopulmonary conditions can be assessed without a clinic visit? In this course, we’ll be focusing on protocols and practical tips to perform a reliable remote cardiopulmonary assessment. Building on your clinical knowledge, we give helpful ways to modify your practice to suit the context of a telehealth video visit. This course will cover many of the areas you’d want to assess after the reporting of a cardiopulmonary complaint. We’ll provide methods to assess respiratory status, jugular venous pressure, and strategies and benefits for remote patient monitoring. To bring it all together, we’ll also provide tips on how to use common wearable devices to gain insights that can help accurately identify maladies and patient status. This course doesn’t assume any previous experience with telehealth or specific technologies but will rely on your previous experience with physical assessments. Whether you are adept at performing telehealth visits or a complete novice, this course contains practices and expert guidance to positively benefit your practice.
ART of the MOOC: Colors, Bodies, Power
Duke University (via Coursera)
Welcome to Art of the MOOC - Colors, Bodies, Power! In this course, you will gain a much more diverse and inclusive understanding of contemporary culture and global art history. Engaging the course's key ideas of colors, bodies and power for their own formal merit and the value of the artworks and artists represented, you will also learn from six experts in the field, learn how key artworks and artistic principles from areas as wide as color theory, performance studies, and cultural theory relate to larger social topics like indigeneity, race, gender, sexuality, and disabilities. Whether you are interested in art and culture for personal or professional reasons, this course will allow you to connect important aspects of your life and practice to some of the most current and relevant aspects of contemporary art and social theory. As one of four in a series, 'Colors, Bodies, Power' complements and enriches the materials covered in the other ART of the MOOC courses.
Decentralized Finance (DeFi) Infrastructure
Duke University (via Coursera)
Decentralized Finance: The Future of Finance is a set of four courses taught by Campbell R. Harvey (Professor of Finance at the Fuqua School of Business, Duke University, and a Research Associate of the National Bureau of Economic Research) that focus on decentralized finance (DeFi). In this first course, we begin by exploring the origins of DeFi and take a broad historical view from the earliest barter economies, such as the first peer-to-peer exchanges of bartering, to present day. The course also looks at historical examples of money having value even though it is not officially backed. We then focus on the key infrastructure components: blockchain, cryptocurrency, smart contracts, oracles, stablecoins and decentralized applications (or dApps). This includes discussion of the mechanics of the Ethereum and Bitcoin blockchains including cryptographic hashing. Next, we focus on the specific problems that DeFi is designed to solve: inefficiency (costly, slow, and insecure today), limited access (1.7 billion are unbanked), opacity (we need to trust regulators to monitor banks and the regulators have mixed records), centralized control (financial system is oligopolistic imposing higher fees than we would have in a competitive market) and lack of interoperability (it is difficult to move funds from one financial institution to another today). The course closes by exploring many of the myths about the crypto space.
Machine Learning Foundations for Product Managers
Duke University (via Coursera)
In this first course of the AI Product Management Specialization offered by Duke University's Pratt School of Engineering, you will build a foundational understanding of what machine learning is, how it works and when and why it is applied. To successfully manage an AI team or product and work collaboratively with data scientists, software engineers, and customers you need to understand the basics of machine learning technology. This course provides a non-coding introduction to machine learning, with focus on the process of developing models, ML model evaluation and interpretation, and the intuition behind common ML and deep learning algorithms. The course will conclude with a hands-on project in which you will have a chance to train and optimize a machine learning model on a simple real-world problem. At the conclusion of this course, you should be able to: 1) Explain how machine learning works and the types of machine learning 2) Describe the challenges of modeling and strategies to overcome them 3) Identify the primary algorithms used for common ML tasks and their use cases 4) Explain deep learning and its strengths and challenges relative to other forms of machine learning 5) Implement best practices in evaluating and interpreting ML models
Think Again II: How to Reason Deductively
Duke University (via Coursera)
Deductive arguments are supposed to be valid in the sense that the premises guarantee that the conclusion is true. In this course, you will learn how to use truth-tables and Venn diagrams to represent the information contained in the premises and conclusion of an argument so that you can determine whether or not the argument is deductively valid. Suggested Readings: Students who want more detailed explanations or additional exercises or who want to explore these topics in more depth should consult Understanding Arguments: An Introduction to Informal Logic, Ninth Edition, Concise, Chapters 6 and 7 by Walter Sinnott-Armstrong and Robert Fogelin. Course Format: Each week will be divided into multiple video segments that can be viewed separately or in groups. There will be short ungraded quizzes after each segment (to check comprehension) and a longer graded quiz at the end of the course.
Financial Risk Management with R
Duke University (via Coursera)
This course teaches you how to calculate the return of a portfolio of securities as well as quantify the market risk of that portfolio, an important skill for financial market analysts in banks, hedge funds, insurance companies, and other financial services and investment firms. Using the R programming language with Microsoft Open R and RStudio, you will use the two main tools for calculating the market risk of stock portfolios: Value-at-Risk (VaR) and Expected Shortfall (ES). You will need a beginner-level understanding of R programming to complete the assignments of this course.
Cloud Virtualization, Containers and APIs
Duke University (via Coursera)
Welcome to the second course in the Building Cloud Computing Solutions at Scale Specialization! In this course, you will learn to design Cloud-native systems with the fundamental building blocks of Cloud computing. These building blocks include virtual machines and containers. You will also learn how to build effective Microservices using technologies like Flask and Kubernetes. Finally, you will analyze successful patterns in Operations including: Effective alerts, load testing and Kaizen. This course is ideal for beginners as well as intermediate students interested in applying Cloud computing to data science, machine learning and data engineering. Students should have beginner level Linux and intermediate level Python skills. For your project in this course, you build a containerized Flask application that is continuously deployed to a Cloud platform: Amazon Web Services (AWS), Azure or Google Cloud Platform (GCP).
Object-Oriented Programming in Python
Duke University (via Coursera)
In this project, you will gain hands-on experience working with classes in Python to model real-world objects and systems. By the end, you will be able to utilize key object-oriented programming principles like inheritance and polymorphism. We will build an interactive boxing match simulation using Python classes to represent different fighters. You will learn how to define class attributes, instantiate object instances, and customize behaviors through methods. The concepts covered translate to building all types of apps.
Data Science Math Skills
Duke University (via Coursera)
Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material. Topics include: ~Set theory, including Venn diagrams ~Properties of the real number line ~Interval notation and algebra with inequalities ~Uses for summation and Sigma notation ~Math on the Cartesian (x,y) plane, slope and distance formulas ~Graphing and describing functions and their inverses on the x-y plane, ~The concept of instantaneous rate of change and tangent lines to a curve ~Exponents, logarithms, and the natural log function. ~Probability theory, including Bayes’ theorem. While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." Good luck and we hope you enjoy the course!
Python Programming Fundamentals
Duke University (via Coursera)
This introductory course is designed for beginners and individuals with limited programming experience who want to embark on their software development or data science journey using Python. Throughout the course, learners will gain a solid understanding of algorithmic thinking, Python syntax, code testing, debugging techniques, and modular code development--essential skills for a successful career in software engineering, development, or data science. By the end of this course, you will learn to: Gain a stepwise approach to problem-solving using algorithms and programming logic. Apply common functions, conditional statements, and loops to build Python scripts and programs. Work with the VS Code programming environment to enhance coding proficiency. Use testing and debugging strategies to ensure code reliability. Perform logical and mathematical operations on datasets. In the final week of the course you will apply your new algorithm design and programming skills to a data analysis problem: analyzing heart rate data.
Investment Evaluation
Duke University (via Coursera)
In this course, you will understand the fundamental principle that money available now is worth more than the same amount in the future due to its potential earning capacity. Additionally, you will master the concepts of Net Present Value (NPV) and breakeven analysis, which allow different cash flows at different periods of time to be compared and summed to determine whether a project is expected to create value. You will apply these concepts by conducting investment evaluations and completing practical assessments on financial projections. This course is ideal for non-financial managers or professionals who seek to enhance their financial acumen to make better business decisions. No prior experience in finance is required. However, a basic understanding of business operations and strategic thinking will be beneficial.
Introduction to Probability and Data with R
Duke University (via Coursera)
This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The concepts and techniques in this course will serve as building blocks for the inference and modeling courses in the Specialization.
Introduction to Generative AI
Duke University (via Coursera)
This introductory course is designed for beginners with no prior knowledge of generative AI. You will start by gaining a high-level understanding of what generative AI is and how it works. Through interactive lessons and hands-on examples, you will learn fundamental skills like providing effective prompts and iteratively improving the generated outputs. As the course progresses, you will dive deeper into specific major generative AI models, including their unique capabilities and limitations. Finally,, you will get practical experience using leading systems like GitHub Copilot, DALL-E, and OpenAI to generate code, images, and text. By the end, you will have developed core knowledge to start experimenting with generative AI in a responsible and effective way for a variety of applications. This course aims to provide a friendly introduction to prepare complete beginners for further exploration of this rapidly evolving technology.
Java Programming: Arrays, Lists, and Structured Data
Duke University (via Coursera)
Build on the software engineering skills you learned in “Java Programming: Solving Problems with Software” by learning new data structures. Use these data structures to build more complex programs that use Java’s object-oriented features. At the end of the course you will write an encryption program and a program to break your encryption algorithm. After completing this course, you will be able to: 1. Read and write data from/to files; 2. Solve problems involving data files; 3. Perform quantitative analyses of data (e.g., finding maximums, minimums, averages); 4. Store and manipulate data in an array or ArrayList; 5. Combine multiple classes to solve larger problems; 6. Use iterables and collections (including maps) in Java.
Rust Axum Greedy Coin Microservice
Duke University (via Coursera)
In this hands-on, 2-hour long project, you will gain practical experience using Rust and Axum to build, test, and deploy a microservice for calculating coin change. Through implementing the greedy algorithm, building API routes and handlers with Axum, and containerizing the web app, you will learn how to rapidly develop services in Rust and deploy them easily across environments. Gain in-demand skills and directly apply them by developing your own functioning microservice start to finish! Task List Implement the greedy coin change algorithm in Rust Create Axum routes for a RESTful web API Make requests to service routes and view JSON responses Containerize the microservice using Docker Explore unit testing for services in Rust Modify and extend the service by adding new features Deploy the container to cloud platforms like AWS and GCP
Scripting with Python and SQL for Data Engineering
Duke University (via Coursera)
In this third course of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will explore techniques to work effectively with Python and SQL. We will go through useful data structures in Python scripting and connect to databases like MySQL. Additionally, you will learn how to use a modern text editor to connect and run SQL queries against a real database, performing operations to load and extract data. Finally, you will use extracted data from websites using scraping techniques. These skills will allow you to work effectively when data is not readily available, or when spatial queries are required to extract useful information from databases.
Medical Neuroscience
Duke University (via Coursera)
Medical Neuroscience explores the functional organization and neurophysiology of the human central nervous system, while providing a neurobiological framework for understanding human behavior. In this course, you will discover the organization of the neural systems in the brain and spinal cord that mediate sensation, motivate bodily action, and integrate sensorimotor signals with memory, emotion and related faculties of cognition. The overall goal of this course is to provide the foundation for understanding the impairments of sensation, action and cognition that accompany injury, disease or dysfunction in the central nervous system. The course will build upon knowledge acquired through prior studies of cell and molecular biology, general physiology and human anatomy, as we focus primarily on the central nervous system. This online course is designed to include all of the core concepts in neurophysiology and clinical neuroanatomy that would be presented in most first-year neuroscience courses in schools of medicine. However, there are some topics (e.g., biological psychiatry) and several learning experiences (e.g., hands-on brain dissection) that we provide in the corresponding course offered in the Duke University School of Medicine on campus that we are not attempting to reproduce in Medical Neuroscience online. Nevertheless, our aim is to faithfully present in scope and rigor a medical school caliber course experience. This course comprises six units of content organized into 12 weeks, with an additional week for a comprehensive final exam: Unit 1 Neuroanatomy (weeks 1-2). This unit covers the surface anatomy of the human brain, its internal structure, and the overall organization of sensory and motor systems in the brainstem and spinal cord. Unit 2 Neural signaling (weeks 3-4). This unit addresses the fundamental mechanisms of neuronal excitability, signal generation and propagation, synaptic transmission, post synaptic mechanisms of signal integration, an...
Programming Fundamentals
Duke University (via Coursera)
Embark on your programming journey! This introductory course teaches you the fundamental principles of programming in C that are applicable to any language you might want to learn. Master a powerful seven-step problem-solving process for developing effective algorithms. Learn to read and understand code, transforming complex challenges into manageable solutions. No prior experience needed. Develop core skills for software development and enhance your career prospects in diverse fields. By the end of this course, you will be able to develop algorithms that are specific and correct.
DevOps, DataOps, MLOps
Duke University (via Coursera)
Learn how to apply Machine Learning Operations (MLOps) to solve real-world problems. The course covers end-to-end solutions with Artificial Intelligence (AI) pair programming using technologies like GitHub Copilot to build solutions for machine learning (ML) and AI applications. This course is for people working (or seeking to work) as data scientists, software engineers or developers, data analysts, or other roles that use ML. By the end of the course, you will be able to use web frameworks (e.g., Gradio and Hugging Face) for ML solutions, build a command-line tool using the Click framework, and leverage Rust for GPU-accelerated ML tasks. Week 1: Explore MLOps technologies and pre-trained models to solve problems for customers. Week 2: Apply ML and AI in practice through optimization, heuristics, and simulations. Week 3: Develop operations pipelines, including DevOps, DataOps, and MLOps, with Github. Week 4: Build containers for ML and package solutions in a uniformed manner to enable deployment in Cloud systems that accept containers. Week 5: Switch from Python to Rust to build solutions for Kubernetes, Docker, Serverless, Data Engineering, Data Science, and MLOps.
Financing for Impact Entrepreneurs
Duke University (via Coursera)
What is the best kind of capital for an impact venture? This course helps you answer that question by exploring the wide range of capital types available to impact-driven enterprises and how to choose the right fit based on your venture’s goals and stage of growth. You’ll begin by learning how the impact investing marketplace has evolved to meet the unique needs of impact entrepreneurs, including the creation of innovative capital structures. Through short, accessible primers, you’ll explore 12 types of impact capital: each with its own benefits, trade-offs, and ideal use cases. By the end of the course, you’ll not only understand the landscape of impact capital, but also gain the tools to evaluate which type best aligns with your venture’s mission, growth stage, and financial strategy. This course is ideal for aspiring and current impact entrepreneurs, managers seeking capital, emerging impact investors, and anyone curious about the growing field of impact investing. No prior experience is required—we break down complex ideas into clear language and provide practical tools and templates to support your learning and application.
Mastering Data Analysis in Excel
Duke University (via Coursera)
This course focuses on essential data analysis using Excel. Learn to design and implement realistic predictive models to reduce uncertainty for informed business decisions. In a hands-on project, you'll act as a business data analyst, building models to assess credit card applications, minimize default risk and maximize bank profits. You'll master key uncertainty measures like classification error rates, entropy of information, and confidence intervals for linear regression. Assignments use data provided within the course and basic Excel functions, ensuring fluency for future business applications. No prior knowledge of advanced Excel features (Visual Basic, Pivot Tables) is required. The Excel and data analysis skills you will learn will enable you to apply business data analysis methods based on binary classification, information theory and entropy measures, and linear regression, and prepare you for roles such as a business data analyst.
Introduction to Machine Learning
Duke University (via Coursera)
This course provides a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) and demonstrates how they can solve complex problems in various industries, from medical diagnostics to image recognition to text prediction. Through hands-on practice exercises, you'll implement these data science models on datasets, gaining proficiency in machine learning algorithms with PyTorch, used by leading tech companies like Google and NVIDIA.
Building Rust AWS Lambda Microservices with Cargo Lambda
Duke University (via Coursera)
In this project, you will learn how to build an AWS Lambda function with Rust using Cargo Lambda. We will create a simple "Marco Polo" Lambda that responds with "Polo" when it receives "Marco" in the request. You will learn: How to create a new Cargo Lambda project Writing a basic Lambda handler function in Rust Building, deploying and invoking your Lambda function locally and on AWS Debugging your Lambda using logging and tracing
Rust Fundamentals
Duke University (via Coursera)
This comprehensive Rust programming course welcomes learners of all levels, including beginners and those with some programming experience. No prior knowledge of Rust is required, making it accessible to coding novices. Throughout the course, you will gain a solid foundation in Rust programming and develop proficiency in advanced concepts, enabling you to write efficient, reliable, and high-performance code. You will understand the core concepts and syntax of Rust, learn effective code organization, error handling techniques, and explore Rust's package manager for efficient project management. By completing this course, you will have the skills to develop reliable and high-performance applications, regardless of your prior programming experience.
Understand Big O Notation in Python
Duke University (via Coursera)
In this 1-hour long project, you will gain first-hand experience using Python to model algorithmic efficiency tradeoffs. By implementing simulations of real-world systems using Big O notation, you will be able to quantify performance impacts of technical and business decisions. This will prepare you to advocate the importance of scale efficiency in data systems you design and maintain.
Blockchain Business Models
Duke University (via Coursera)
Blockchain is an emerging and highly disruptive technology that is poorly understood. In this course you will learn what blockchain is and how it can create value by tokenization in cryptocurrencies and in many other practical applications. The applications include: stablecoins (like Facebook’s Libra and JP Morgan’s JPMCoin), machine to machine payments, identity protection, supply chain management (Walmart, Maersk, IBM), secure voting, distributed exchanges, decentralized finance, property transfers, central bank fiat crypto (e.g., Fedcoin and China’s digital Renminbi), dispensing prescription drugs, private records, intellectual property, financial reporting, and media and advertising, to name a few. The goals of the course are to: (i) provide an advanced understanding of the various blockchain technologies; (ii) determine the specific business situations where blockchain technology can be deployed to solve important problems; (iii) select the specific blockchain technology that has the best chance of success for a particular problem; and (iv) detail the risks presented by this new technology.
Building an Agile Culture for Your Organization
Duke University (via Coursera)
In this course, you will learn how to build an agile culture that embraces change and fosters innovation. You will explore the key attributes of an agile culture and understand how leaders can reduce barriers to agility within their teams and organizations. This module will provide insights into the leadership mindset required to embed agility into your organization’s culture, enabling it to adapt and thrive in dynamic environments. This module is ideal for leaders who want to drive cultural agility and foster an environment of continuous transformation. No prior experience in cultural agility is required.
Civic Engagement in American Democracy
Duke University (via Coursera)
So how does the American political system work? Who are some of the key actors? What are key concepts for a student trying to understand what’s going on? How can I as a citizen influence politics? Civic Engagement in American Democracy takes on these and other key questions. We’re Dr. Nicholas Carnes and Dr. Bruce Jentleson, the principal course instructors. Along with our Duke faculty colleagues who also contributed modules, we’ve designed the course to provide a strong foundational introduction to US politics. If you’re new to this material, proceed through the modules one by one and build up your knowledge of politics and government. If some of the material is familiar, go ahead and set your own pace. Either way we hope Civic Engagement in American Democracy helps you be an effective student in more advanced politics courses and/or an engaged citizen in 21st century America.
Introductory Human Physiology
Duke University (via Coursera)
Explore the fascinating world of human physiology and learn about the body's organ systems, their functions, and how they maintain health. In this comprehensive course, you will: Master key concepts in human physiology and homeostasis Delve into the nervous, endocrine, cardiovascular, respiratory, and urinary systems Examine the role of senses, muscles, gastrointestinal, and reproductive systems Apply knowledge to real-life situations and medical conditions This course is perfect for students, healthcare professionals, and anyone interested in human physiology and biology, building upon a basic understanding of human anatomy. This course is an excellent resource for MCAT preparation or as a refresher for health professionals. As a bonus, enhance your learning with a unique immersive virtual reality (VR) experience, accessible on both VR and desktop platforms, that takes you on an incredible journey inside the human body. This course offers a captivating way to explore and understand complex physiological concepts, as you virtually shrink to navigate through blood vessels and then return to normal size to measure blood pressure. The course comes to life as an educational adventure.
ESG Essentials for Sustainable Business
Duke University (via Coursera)
This beginner-friendly course provides a foundational introduction to Environmental, Social, and Governance (ESG) principles and their critical role in addressing global environmental and societal challenges. Participants will explore ESG’s growing importance in business and policy, learn key terminology, and gain insights into major players in the ESG landscape. Designed for individuals across all roles and industries, this course equips learners with the knowledge needed to navigate the evolving world of sustainable practices and lay the groundwork for impactful ESG initiatives.
Databricks to Local LLMs
Duke University (via Coursera)
By the end of this course, a learner will master Databricks to perform data engineering and data analytics tasks for data science workflows. Additionally, a student will learn to master running local large language models like Mixtral via Hugging Face Candle and Mozilla llamafile.
Copyright for Educators & Librarians
Duke University (via Coursera)
Fear and uncertainty about copyright law often plagues educators and sometimes prevents creative teaching. This course is a professional development opportunity designed to provide a basic introduction to US copyright law and to empower teachers and librarians at all grade levels. Course participants will discover that the law is designed to help educators and librarians.
Build a Static Website with Rust and Zola
Duke University (via Coursera)
In this project, you will learn how to use the Zola static site generator to build and deploy a fast, secure static website. You will install Zola, create a site structure, incorporate themes and templates, customize content and configuration, and deploy the final site to a cloud hosting platform. By the end of the project, you will have hands-on experience building a production-ready site with Zola that can be used for personal or professional use cases.
Python Scripting
Duke University (via Coursera)
In this 2-hour long project-based course, you will learn how to create command line interface tools using Python. You will use standard library modules like sys and subprocess to parse arguments and run external commands. You will also learn how to process raw command output in Python to filter and format results. By the end, you will be able to build basic but practical CLI utilities using only Python to automate tasks and workflows.