University of Washington
Public University • US
Showing 45 courses from UW
Introduction to Public Speaking - University of Washington
University of Washington (via Coursera)
Introduction to Public Speaking - University of Washington is a comprehensive beginner-level resource offered by University of Washington, 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: 20 hours of content, designed to be completed in 2-4 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: 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 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. University of Washington 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 - University of Washington
University of Washington (via Coursera)
Introduction to Public Speaking - University of Washington is a comprehensive beginner-level resource offered by University of Washington, 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: 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 English and communication Freelancers wanting to add new services to their portfolio Self-learners passionate about English and communication 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 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. University of Washington 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.
Business English Specialization - University of Washington
University of Washington (via Coursera)
Business English Specialization - University of Washington is a comprehensive intermediate-level resource offered by University of Washington, 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: 60 hours of content, designed to be completed in 6-12 weeks at a comfortable pace. Basic familiarity with the subject area is recommended. You should have completed a beginner-level course or have equivalent self-taught knowledge. Comfort with using a computer and basic problem-solving skills will help. 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: 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 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. University of Washington 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.
Business Law: A Community of Practice with Paralegals
University of Washington (via Coursera)
Business Law is a significant part of many legal practices. As a paralegal, you may work in one or more areas of business law. This short course will equip you with a solid grasp of how agency relationships work—including how to spot legal risks when they go sideways. You'll get hands-on with real-world business structures, learning when it makes sense to form an LLC versus a partnership, and how to avoid those dreaded partnership disputes. Plus, you'll navigate the world of corporations—from incorporation to boardroom accountability—so you can confidently support clients through business growth, governance, and even mergers. This course is designed as an introductory overview and not a ‘one-stop shop’ for in-depth legal education. Understanding each aspect of these specialized areas—would require much more time and study. Each lesson has a reading assignment, case scenarios (practice assessments) and a graded quiz. These activities will help you reinforce what you have learned. The course will require you to practice basic legal writing and analytical skills that you apply towards case scenario assignments to strengthen your case analysis skills. Remember to monitor business law trends as the business laws presented in this course are likely to change over time.
머신 러닝: 회귀 모델
University of Washington (via Coursera)
사례 연구 - 주택 가격 예측 첫 번째 사례 연구 주택 가격 예측에서는 입력 특성(면적, 방 및 화장실 개수 등)에서 연속적인 값(가격)을 예측하는 모델을 만듭니다. 이는 회귀를 적용할 수 있는 많은 장소 중 하나일 뿐입니다. 그 외 다른 응용의 범위는 의약품에 대한 건강 효과, 금융 분야에서의 주가, 고성능 컴퓨터 전력 사용 예측에서부터 유전자 발현에 중요한 조절기를 분석하는 것까지 다양합니다. 본 강의에서는 예측 및 특성 선택 태스크를 위한 정규화된 선형 회귀 모델에 대해 알아봅니다. 매우 큰 특성의 집합을 처리하고 다양한 복잡도 모델 중 선택할 수 있습니다. 또한 이상치와 같은 데이터의 양상이 선택한 모델과 예측값에 주는 영향도 분석합니다. 이와 같은 모델을 피팅하기 위해 큰 데이터 세트에 따라 확장하는 최적화 알고리즘을 구현해 봅니다. 학습 목표: 본 강의를 끝내면 여러분은: -회귀 모델의 입력과 출력을 설명할 수 있습니다. -데이터를 모델링할 때 편향과 분산을 비교 및 대조할 수 있습니다. -최적화 알고리즘을 사용하여 모델 매개변수를 예상할 수 있습니다. -교차 검증을 사용하여 매개변수를 조정할 수 있습니다. -모델의 성능을 분석할 수 있습니다. -희소성의 개념과 라쏘가 희소 해로 이어지는 방법을 설명할 수 있습니다. -모델 중 선택할 방법을 배포할 수 있습니다. -모델을 활용하여 예측을 형성할 수 있습니다. -주택 데이터 세트를 사용하여 가격을 예측하는 회귀 모델을 구축할 수 있습니다. -이와 같은 기술을 Python에서 구현할 수 있습니다.
Lesson | Business English Skills: Introducing Yourself in Business Settings
University of Washington (via Coursera)
This lesson is part of a full course, Business English Networking. Take this lesson to get a short tutorial on the learning objectives covered. To dive deeper into this topic, take the full course. By the end of this lesson, you will be able to: Introduce yourself by giving your name, job, company, and city Identify the job, company, and the city of new acquaintances
Essential Marketing Frameworks
University of Washington (via Coursera)
This course will give you an introduction to key marketing concepts and basic skills. You’ll learn how tools such as marketing frameworks can help you analyze the market and achieve business goals. As you dive into the psychology of marketing, you’ll learn how to understand consumer behavior, size up the competition, and engage customers through effective marketing channels. This course will provide you with the foundational knowledge needed to explore more specialized marketing topics.
Lesson | Business English Skills: How to Navigate Tone, Formality, and Directness in Emails
University of Washington (via Coursera)
This lesson is part of a full course, Business English Networking. Take this lesson to get a short tutorial on the learning objectives covered. To dive deeper into this topic, take the full course. By the end of this lesson, you will be able to: Distinguish between formal and informal language Distinguish between direct and indirect language Choose the appropriate tone based on your relationship with your recipient, the context, and request
Ukraine: History of Civil Society
University of Washington (via Coursera)
This course presents social and political events and processes that occurred when the Ukrainian civil society was forming. On February 24, 2022, the global attention was focused on Ukraine. Then organized civil society started its aid to Ukrainian armed forces, which surprised not only foreigners but even Ukrainians themselves. How did Ukrainian society prove to be stable, self-organized, and capable of effective resistance to a much greater threat? Why have Ukrainians united, acted, and gone to street protests starting from the early 90s? What values did they protect? This course will help you understand the nature of Ukrainian revolutions and the phenomenon of mass resistance, and also values motivating Ukrainians to act in the context of their independence. In this course, you will learn: a short historical insight into the manifestation of Ukrainian values from the 1990s until now; Orange Revolution, its prerequisites, course of events, and main participants; establishment and development of independent Ukrainian media; the reasons and prerequisites of the Revolution of Dignity – a protest that transformed the entire state system of rules and the institutional environment; the concept of multiculturalism and its implementation in Ukraine; the political and public life of Crimean Tatars in Ukraine, as well as Russia's crimes on the territory of Crimea; the history of Ukrainian civil movements and communities in the East of Ukraine; the power and influence of the society's unity during crisis. PRESENTERS Kateryna Zarembo PhD, Research Fellow at the Central European University and the Technical University of Darmstadt, Associated Fellow at the New Europe Center Tymofii Brik PhD, Rector at the Kyiv School of Economics COURSE AUTHORS: Oleksandra Matviichuk human rights lawyer and chair of the Center for Civil Liberties organization, was awarded the Nobel Peace Prize in 2022 Vakhtang Kebuladze Doctor of Phi...
Machine Learning Foundations: A Case Study Approach
University of Washington (via Coursera)
Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python.
Business English: Making Presentations
University of Washington (via Coursera)
This course teaches you language and techniques that will help you make effective presentations in English. The final task is to develop a well-organized, persuasive presentation using charts and graphs that sells your city as a venue. The course focuses on students who have an intermediate level of English, with a minimum of two years of formal language study. Course Learning Objectives • Present information in an organized and engaging way • Share data in charts and graphs • Use persuasive language in a presentation
Business English: Planning & Negotiating
University of Washington (via Coursera)
In this course, the context is hosting an event and finding an appropriate venue for it. You will learn language and strategies for successful negotiations culminating in a written announcement for an event. Course Learning Objectives • Negotiate strategically in formal and informal settings • Identify and resolve customer issues after a negotiation has taken place • Evaluate and compare services and features of two venues • Plan a business event using negotiation skills • Write an announcement for a business event after selecting a venue
Power BI Basics: Requirements to Visualizations
University of Washington (via Coursera)
Welcome to the Power BI Essentials course! Our world is changing, and today’s businesses rely on data to do many things; and that includes using data to illustrate insights that captures more dimensions of what’s happening with their customers, products, services and the world around us. This beginner-friendly Power BI course is designed to help you master the essentials of getting started with using the Power BI interface, navigating the relevance of business requirements gathering and using Power Query and other basic features to connect, combine and transform data. We do recommend some basic experience using Microsoft Excel as this is the primary application we will use for uploading data to Power BI. With engaging video lessons, hands-on practice exercises, and interactive quizzes; you’ll master the foundations to grow your business intelligence as you continue to deepen your knowledge with more advanced Power BI Visualizations courses offered at the University of Washington.
Social Media Data Analytics
University of Washington (via Coursera)
Learner Outcomes: After taking this course, you will be able to: Utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr. Process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data. Analyze unstructured data - primarily textual comments - for sentiments expressed in them. Use different tools for collecting, analyzing, and exploring social media data for research and development purposes. Sample Learner Story: Data analyst wanting to leverage social media data. Isabella is a Data Analyst working as a consultant for a multinational corporation. She has experience working with Web analysis tools as well as marketing data. She wants to now expand into social media arena, trying to leverage the vast amounts of data available through various social media channels. Specifically, she wants to see how their clients, partners, and competitors view their products/services and talk about them. She hopes to build a new workflow of data analytics that incorporates traditional data processing using Web and marketing tools, as well as newer methods of using social media data. Sample Job Roles requiring these skills: Social Media Analyst Web Analyst Data Analyst Marketing and Public Relations Final Project Deliverable/ Artifact: The course will have a series of small assignments or mini-projects that involve data collection, analysis, and presentation involving various social media sources using the techniques learned in the class. The course was developed by Dr. Chirag Shah while he was a faculty member at Rutgers University. He is currently a faculty member at University of Washington.
Data Science at Scale - Capstone Project
University of Washington (via Coursera)
In the capstone, students will engage on a real world project requiring them to apply skills from the entire data science pipeline: preparing, organizing, and transforming data, constructing a model, and evaluating results. Through a collaboration with Coursolve, each Capstone project is associated with partner stakeholders who have a vested interest in your results and are eager to deploy them in practice. These projects will not be straightforward and the outcome is not prescribed -- you will need to tolerate ambiguity and negative results! But we believe the experience will be rewarding and will better prepare you for data science projects in practice.
Programming Languages, Part B
University of Washington (via Coursera)
[As described below, this is Part B of a 3-part course. Participants should complete Part A first -- Part B "dives right in" and refers often to material from Part A.] This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones. This course is neither particularly theoretical nor just about programming specifics -- it will give you a framework for understanding how to use language constructs effectively and how to design correct and elegant programs. By using different languages, you will learn to think more deeply than in terms of the particular syntax of one language. The emphasis on functional programming is essential for learning how to write robust, reusable, composable, and elegant programs. Indeed, many of the most important ideas in modern languages have their roots in functional programming. Get ready to learn a fresh and beautiful way to look at software and how to have fun building it. The course assumes some prior experience with programming, as described in more detail in the first module of Part A. Part B assumes successful completion of Part A. The course is divided into three Coursera courses: Part A, Part B, and Part C. As explained in more detail in the first module of Part A, the overall course is a substantial amount of challenging material, so the three-part format provides two intermediate milestones and opportunities for a pause before continuing. The three parts are designed to be completed in order and set up to motivate you to continue through to the end of Part C. Week 1 of Part A has a more detailed list of topics for all three parts of the course, but it is expected that most course participants will not (yet!) k...
Business English: Networking
University of Washington (via Coursera)
This course begins with a welcome message and an overview of the Specialization. After this introduction, you will be asked to take a proficiency test to see if this course is right for you. During the course, you will begin learning vocabulary and customs related to socializing and networking in English. The goal is to enable you to interact with business contacts in person, on the phone and over email in a professional way. Course Learning Objectives • Determine whether the objectives of this Specialization align with your learning goals • Evaluate your current level of proficiency in business English communication • Present relevant information about yourself in a discussion forum • Develop your networking skills • Write short emails with appropriate formatting • Recognize and produce formal and informal language in emails • Develop vocabulary related to jobs and companies
Designing Autonomous AI
University of Washington (via Coursera)
(This program was formerly part of a three-course specialization called Autonomous AI for Industry. Because the software program Bonsai was discontinued, references to Bonsai have been removed. You can still learn about autonomous AI and machine teaching through our two individual courses "Designing Autonomous AI" and "Machine Teaching for Autonomous AI.") To design an autonomous AI system, you must figure out how to distill a business challenge into its component parts. When children learn how to hit a baseball, they don’t start with fastballs. Their coaches begin with the basics: how to grip the handle of the bat, where to put their feet and how to keep their eyes on the ball. Similarly, an autonomous AI system needs a subject matter expert (SME) to break a complex process or problem into easier tasks that give the AI important clues about how to find a solution faster. In this course, you’ll learn how to create an autonomous AI design plan. By setting goals, identifying trainable skills, and employing those skills in goal-oriented strategies, you’ll incorporate your SME’s knowledge directly into your AI’s “brain,” the agent that powers your autonomous system. You'll learn when and how to combine various AI architecture design patterns, as well as how to design an advanced AI at the architectural level without worrying about the implementation of neural networks or machine learning algorithms. At the end of this course, you’ll be able to: • Interview SMEs to extract their unique knowledge about a system or process • Combine reinforcement learning with expert rules, optimization and mathematical calculations in an AI brain • Design an autonomous AI brain from modular components to guide the learning process for a particular task • Validate your brain design against existing expertise and techniques for solving problems • Produce a detailed specifications document so that someone else can build your AI brain
NOC:Applied Accelerated Artificial Intelligence
IIT Guwahati KLE Technological University NVIDIA (via NPTEL)
NOC:Applied Accelerated Artificial Intelligence — a free online course offered by IIT Guwahati KLE Technological University NVIDIA through the NPTEL platform. Taught by Prof. Adesuyi Tosin, Prof. Bharatkumar Sharma, Prof. Satyadhyan Chickerur, Prof. Satyajit Das. This is an intermediate-level course designed for undergraduate and postgraduate students. Estimated duration: 30 hours (~4 days). Category: AI & Machine Learning. Certification available through SWAYAM with a nominal exam fee. All video lectures, assignments, and course materials are freely accessible.
Project Management Quickstart
University of Washington (via Coursera)
Thinking about project management as a career? Or maybe you’ve just been asked to manage a project and need a quick crash course. This beginner-friendly class is your launchpad. In just a few weeks, you’ll learn the basics of project management through a real-world Agile scenario. You’ll create professional-grade artifacts—a project charter, work breakdown structure (WBS), and project roadmap—that you can add to your portfolio and showcase on your resume. Along the way, you’ll sharpen essential soft skills like leadership, communication, and problem-solving. Learn how to manage stakeholders, navigate team dynamics, and tackle challenges with confidence. You’ll see how projects come to life, from kickoff to delivery, and gain practical tools and techniques that you can apply right away. Whether you’re exploring project management as a new career or just want to be a stronger team player, this course will give you the confidence to stand out. Take the first step toward a more organized, impactful, and successful future—you’ll thank yourself later.
Machine Learning: Regression
University of Washington (via Coursera)
Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets. Learning Outcomes: By the end of this course, you will be able to: -Describe the input and output of a regression model. -Compare and contrast bias and variance when modeling data. -Estimate model parameters using optimization algorithms. -Tune parameters with cross validation. -Analyze the performance of the model. -Describe the notion of sparsity and how LASSO leads to sparse solutions. -Deploy methods to select between models. -Exploit the model to form predictions. -Build a regression model to predict prices using a housing dataset. -Implement these techniques in Python.
Programming Languages, Part A
University of Washington (via Coursera)
This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones. This course is neither particularly theoretical nor just about programming specifics -- it will give you a framework for understanding how to use language constructs effectively and how to design correct and elegant programs. By using different languages, you will learn to think more deeply than in terms of the particular syntax of one language. The emphasis on functional programming is essential for learning how to write robust, reusable, composable, and elegant programs. Indeed, many of the most important ideas in modern languages have their roots in functional programming. Get ready to learn a fresh and beautiful way to look at software and how to have fun building it. The course assumes some prior experience with programming, as described in more detail in the first module. The course is divided into three Coursera courses: Part A, Part B, and Part C. As explained in more detail in the first module of Part A, the overall course is a substantial amount of challenging material, so the three-part format provides two intermediate milestones and opportunities for a pause before continuing. The three parts are designed to be completed in order and set up to motivate you to continue through to the end of Part C. The three parts are not quite equal in length: Part A is almost as substantial as Part B and Part C combined. Week 1 of Part A has a more detailed list of topics for all three parts of the course, but it is expected that most course participants will not (yet!) know what all these topics mean.
Ukraine: History, Culture and Identities
University of Washington (via Coursera)
Explore the history, culture and society of the people of Ukraine from the Middle Ages to the present in this introductory course developed by the Ukrainian Institute, educational studio EdEra, and the National University of Kyiv-Mohyla Academy and offered on Coursera in cooperation with the University of Washington. The culture and identities of Ukrainian people have existed in this region for more than a thousand years. Like most Eastern European countries, Ukraine is a rather young country — it declared its independence in 1991. Since then, it managed to survive three revolutions struggling for the protection of democratic values and human rights; radically changed the vector of international politics; and advanced significantly in the development of arts and culture. Learn about the events and processes that took place before independence was declared and see what historical and cultural heritage was preserved by the Ukrainian people when it entered the 21st century in this program taught by researchers, experts in history and political science, and professors from the National University of Kyiv-Mohyla Academy. Dr. Natalia Shlikhta, Associate Professor, Head of the Department of History, National University of Kyiv-Mohyla Academy Dr. Maksym Yakovlev, Head of the Department of International Relations, National University of Kyiv-Mohyla Academy, Director of the School for Policy Analysis Dr. Tetiana Grygorieva, Associate Professor of the Department of History, National University of Kyiv-Mohyla Academy Dr. Vadym Aristov, Senior lecturer of the Department of History, National University of Kyiv-Mohyla Academy Dr. Kateryna Dysa, Associate Professor of the Department of History, National University of Kyiv-Mohyla Academy
Business English: Meetings
University of Washington (via Coursera)
This course will teach you vocabulary and skills related to participating in meetings. You will learn terms and phrases used both in email and in speaking to arrange, participate in, and conclude meetings. The goals of this course are to enable you to participate effectively in on-site meetings and teleconferences and to prepare you to write a proposal as an outcome of a meeting. Course Learning Objectives • Arrange a meeting though email and by telephone • List expectations and protocols related to on-site meetings and teleconferences • State phone numbers, dates, currencies and sales figures accurately • Write a proposal with appropriate organization and vocabulary
Machine Learning: Classification
University of Washington (via Coursera)
Case Studies: Analyzing Sentiment & Loan Default Prediction In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank. These tasks are an examples of classification, one of the most widely used areas of machine learning, with a broad array of applications, including ad targeting, spam detection, medical diagnosis and image classification. In this course, you will create classifiers that provide state-of-the-art performance on a variety of tasks. You will become familiar with the most successful techniques, which are most widely used in practice, including logistic regression, decision trees and boosting. In addition, you will be able to design and implement the underlying algorithms that can learn these models at scale, using stochastic gradient ascent. You will implement these technique on real-world, large-scale machine learning tasks. You will also address significant tasks you will face in real-world applications of ML, including handling missing data and measuring precision and recall to evaluate a classifier. This course is hands-on, action-packed, and full of visualizations and illustrations of how these techniques will behave on real data. We've also included optional content in every module, covering advanced topics for those who want to go even deeper! Learning Objectives: By the end of this course, you will be able to: -Describe the input and output of a classification model. -Tackle both binary and multiclass classification problems. -Implement a logistic regression model for large-scale classification. -Create a non-linear model using decision trees. -Improve the performance of any model using boosting. -Scale your methods with s...
NOC:Computational Gas Dynamics
IIT Kanpur IIT Guwahati (via NPTEL)
NOC:Computational Gas Dynamics — a free online course offered by IIT Kanpur IIT Guwahati through the NPTEL platform. Taught by Prof. Niranjan Sahoo, Prof. Rajesh Ranjan. This is an intermediate-level course designed for undergraduate and postgraduate students. Estimated duration: 30 hours (~4 days). Category: Programming & DSA. Certification available through SWAYAM with a nominal exam fee. All video lectures, assignments, and course materials are freely accessible.
Speaking to persuade: Motivating audiences with solid arguments and moving language
University of Washington (via Coursera)
In the professional realm, we need to be able to argue without being argumentative. Whether you are fundraising for a nonprofit, pitching a business proposal, or suggesting a change to company policy, you are making arguments. In making the case for your topic, you often want to raise awareness, identify a pressing problem, discuss appropriate solutions, and outline specific steps for the audience. To be persuasive, you must be clear (the audience may have little to no existing knowledge), you must be convincing (you are trying to sway the audience that your argument is valid), and you must be compelling (you are trying to motivate the audience enough so that they want to take specific actions). Persuasive speaking thus requires clarity, strategy, topic mastery, plus a sense of style and presence. By the end of this course, you should be able to design persuasive speeches that address problems and solutions and that motivate audience members. You should be able to use rhetorical style strategically and deliver passionate and compelling speeches. Learners will record speeches, providing and receiving peer feedback.
Creating Responsive Websites for Any Device
University of Washington (via Coursera)
In this course your web design skills go from good to great. This course is all about responsive design—creating layouts that look just as killer on a smartphone as they do on a desktop. You’ll dive into Flexbox and Grid, the CSS superheroes that make flexible, adaptive designs possible. And with media queries, you’ll fine-tune every pixel, making sure your sites look sharp no matter the screen size. But it’s not just about the code. This course gives you hands-on experience designing for real-world audiences. You’ll test, optimize, and learn best practices for making accessible, visually appealing layouts that stand out. By the end, you won’t just know how to code responsive sites—you’ll know how to think like a pro designer, giving users the best experience on any device.
Computational Neuroscience
University of Washington (via Coursera)
This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.
Guided Website Development Project
University of Washington (via Coursera)
This course is where things get real. This is your chance to put all those HTML, CSS, and responsive design skills to work on a project that simulates the real deal—a professional website for a client. Imagine you’re a freelance developer, hired to create a site from scratch. You’ll start by diving into client requirements, mapping out user stories, and building a structure that brings the client’s vision to life. From there, it’s all about rolling up your sleeves and making the magic happen with the tools and techniques you’ve mastered. But here’s the kicker: this isn’t just a follow-the-instructions project. It’s guided, yes, but we want you to get creative, push boundaries, and explore beyond what’s covered. Plus, you’ll learn how smart developers collaborate with AI to streamline workflows and spark new ideas. Your project will also be peer-reviewed, so you’ll get valuable feedback and see how other people tackled the same challenge. At the finish line, you’ll have a multi-page website ready to wow clients and beef up your portfolio. This course is your chance to prove you’re not just learning web dev—you’re living it.
Programming Languages, Part C
University of Washington (via Coursera)
[As described below, this is Part C of a 3-part course. Participants should complete Parts A and B first -- Part C "dives right in" and refers often to material from Part A and Part B.] This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones. This course is neither particularly theoretical nor just about programming specifics -- it will give you a framework for understanding how to use language constructs effectively and how to design correct and elegant programs. By using different languages, you will learn to think more deeply than in terms of the particular syntax of one language. The emphasis on functional programming is essential for learning how to write robust, reusable, composable, and elegant programs. Indeed, many of the most important ideas in modern languages have their roots in functional programming. Get ready to learn a fresh and beautiful way to look at software and how to have fun building it. The course assumes some prior experience with programming, as described in more detail in the first module of Part A. Part B assumes successful completion of Part A. The course is divided into three Coursera courses: Part A, Part B, and Part C. As explained in more detail in the first module of Part A, the overall course is a substantial amount of challenging material, so the three-part format provides two intermediate milestones and opportunities for a pause before continuing. The three parts are designed to be completed in order and set up to motivate you to continue through to the end of Part C. Week 1 of Part A has a more detailed list of topics for all three parts of the course, but it is expected that most course participants...
Building Web Pages with HTML & CSS
University of Washington (via Coursera)
If you’re ready to dive into the world of web development, this course is your launchpad. Whether you’re a graphic designer itching to build the sites you mock up, an instructional designer wanting to finesse HTML in your LMS, an entrepreneur looking to put your business online, or just developing skills for a side hustle—this course is for you. Taught by real-deal front-end developers who’ve cut their teeth on websites for top tech and e-tail companies, you’re learning from the best right here in Seattle. This course covers the essentials, guiding you through single-page HTML and CSS files. You’ll get hands-on with Git and GitHub, learning version control and how to host your projects like a pro on GitHub Pages. And it doesn’t stop there—your instructors are packed with insider tips, straight from years of industry experience, to give you a leg up. By the end, you’ll not only know how to write solid HTML and CSS but also how to handle AI-generated code like a champ. And the best part? You’ll create your own single-page website on any topic you choose, turning theory into real-world skills. This isn’t just about learning code—it’s about getting in the game.
U101: Understanding College and College Life
University of Washington (via Coursera)
College can be confusing and intimidating, but U101 can help. If you were just admitted to college and are nervous about what the next step in life might look like, this course is for you. If you are the parent of a newly admitted college student and curious about what college life is like, this course is also for you. While your specific college will, no doubt, provide additional orientation material, we wanted to give some basic information about what life might be like at a large American University. You might be years away from college or enrolled right now; either way, U101 has some excellent advice from college students, professors, administrators, and staff. At the conclusion of the course, learners should: 1. Understand the basics of how colleges and universities operate. 2. Identify and describe what faculty are looking for in college-level academic work. 3. List some effective study strategies. 4. Identify some strategies for exploring and selecting a major. 5. Identify the various types of grants and scholarships available and describe the steps involved in applying to these. 6. Discuss the college life, with special attention to the benefits/limitations of living on or off campus. 7. Identify some strategies for getting the most out of campus life activities (investigating student clubs, fraternities, sororities, etc.). The course is divided into 4 weeks/8 lessons, which provide an overview of the different aspects of college life. If you were just watching the videos and looking at some of the links, the whole course would take about 4-5 hours. Week 1 Lesson 1. Welcome to U101! Lesson 2. Understanding the Nature of College Week 2 Lesson 3. Succeeding as a Student Lesson 4. Building Your Major Week 3 Lesson 5. Financing Your Education Lesson 6. Living On and Off Campus Week 4 Lesson 7. Getting Involved in Campus Life Lesson 8. Conclusion Please join us for a short exploration of modern American Colleges. Hopefully, this course can help dem...
Business English: Capstone Project
University of Washington (via Coursera)
The capstone project will give you opportunities to demonstrate your competence in the learning objectives for this Specialization. For the project, you’ll use formal, written methods and more casual visual and audio methods of communication to demonstrate your ability to use language appropriate for different business contexts. The goal of this course is to demonstrate competence in writing and presenting a plan using skills and language appropriate for business. Course Learning Objectives • Use appropriate vocabulary to write a mini business plan • Communicate a business plan orally in an organized and engaging presentation
머신 러닝 기초: 사례 연구 접근 방식
University of Washington (via Coursera)
데이터가 있고 그 데이터로 무엇을 알 수 있는지 궁금하신가요? 머신 러닝으로 비즈니스를 개선할 수 있는 핵심 방법을 더 깊이 이해해야 하나요? 회귀 및 분류에서 딥 러닝 및 추천 시스템까지 어떤 내용으로든 전문가와 대화할 수 있기를 원하시나요? 이 과정에서는 일련의 실제 사례 연구를 통해 머신 러닝에 대한 실무 경험을 얻을 수 있습니다. 첫 번째 과정이 끝나면 주택 수준 특성을 기반으로 주택 가격을 예측하고, 사용자 리뷰에서 감정을 분석하고, 관심 문서를 검색하고, 제품을 추천하고, 이미지를 검색하는 방법을 배우게 됩니다. 이러한 사용 사례에 대한 실습을 통해 광범위한 영역에서 머신 러닝 방법을 적용할 수 있습니다. 이 첫 번째 과정은 머신 러닝 방법을 블랙박스로 취급합니다. 이 추상화를 통해 관심 있는 작업을 이해하고, 이러한 작업을 머신 러닝 도구와 일치시키고, 출력 품질을 평가하는 데 집중할 것입니다. 후속 과정에서는 모델과 알고리즘을 검토하여 이 블랙박스의 구성 요소를 자세히 알아볼 것입니다. 이 조각들은 결합하여 지능형 애플리케이션 개발에 사용할 머신 러닝 파이프라인을 형성합니다. 학습 결과: 이 과정을 마치면 다음을 수행할 수 있습니다. -실제로 머신 러닝의 잠재적 애플리케이션을 식별합니다. -회귀, 분류 및 클러스터링을 통해 가능해진 분석의 핵심 차이를 설명합니다. -잠재적 애플리케이션에 적합한 머신 러닝 작업을 선택합니다. -회귀, 분류, 클러스터링, 검색, 추천 시스템 및 딥 러닝을 적용합니다. -머신 러닝 모델에 대한 입력 정보 역할을 하는 특성으로 데이터를 제시합니다. -각 작업에 대한 관련 오류 지표 측면에서 모델 품질을 평가합니다. -새로운 데이터를 분석하기 위해 모델에 맞는 데이터 세트를 활용합니다. -머신 러닝을 핵심으로 사용하는 엔드 투 엔드 애플리케이션을 구축합니다. -Python에서 이러한 기술을 구현합니다.
الخطابة الإقناعية: تحفيز الجماهير بالحجج المُقنِعة واللغة المؤثِّرة
University of Washington (via Coursera)
في المجال المهني، يجب أن نكون قادرين على برهنة أفكارنا بالحجج المنطقية بدون الدخول في مواضع جدال أو نزاع. سواء كنت تسعى إلى جمع الأموال لمنظمات غير ربحية، أو تقديم عرض عمل، أو اقتراح تغيير في سياسة الشركة، فعليك أن تُبرهِن على صحة حججك للنجاح في مسعاك. لذا، يجب أن يكون هدفك أثناء عرض موضوعك زيادة الوعي، وتحديد المشكلات الملِّحة، ومناقشة الحلول المناسبة، وتحديد خطوات معيَّنة للجمهور. ولكي تكون مُقنِعًا، يجب أن تكون واضحًا في عرض أفكارك (فربما يتمتع الجمهور بمعرفة قليلة عن الموضوع أو قد لا يدري أي شيء عنه على الإطلاق)، ويجب أن تكون أفكارك دامغة (من خلال محاولتك التأثير على جمهورك وإقناعهم أنّ حجتك صحيحة ومنطقية)، ويجب أيضًا أن يكون أسلوبك حاسمًا (من خلال تحفيز الجمهور بما فيه الكفاية حتى تلمس رغبة الناس في اتخاذ إجراءات محددة). وبالتالي، تتطلَّب الخطابة الإقناعية عرض أفكار واضحة ووضع إستراتيجية فعّالة والإلمام الشامل بالموضوع المطروح، بالإضافة إلى التمتُّع بشخصية وحضور قويين. عند انتهاء هذه الدورة التدريبية، ستتمكَّن من وضع خُطَب إقناعية تستعرض أي مشكلة وحلولها وتحفِّز الجمهور. وستتمكَّن من استخدام الأساليب البلاغية بصورة إستراتيجية وإلقاء خُطَب حماسية ومُقنِعة. سيسجِّل الدارسون الخُطَب وسيتبادلون الملاحظات مع زملائهم.
Machine Teaching for Autonomous AI
University of Washington (via Coursera)
(This program was formerly part of a three-course specialization called Autonomous AI for Industry. Because the software program Bonsai was discontinued, references to Bonsai have been removed. You can still learn about autonomous AI and machine teaching through our two individual courses "Designing Autonomous AI" and "Machine Teaching for Autonomous AI.") Just as teachers help students gain new skills, the same is true of artificial intelligence (AI). Machine learning algorithms can adapt and change, much like the learning process itself. Using the machine teaching paradigm, a subject matter expert (SME) can teach AI to improve and optimize a variety of systems and processes. The result is an autonomous AI system. In this course, you’ll learn how automated systems make decisions and how to approach designing an AI system that will outperform current capabilities. Since 87% of machine learning systems fail in the proof-concept phase, it’s important you understand how to analyze an existing system and determine whether it’d be a good fit for machine teaching approaches. For your course project, you’ll select an appropriate use case, interview a SME about a process, and then flesh out a story for why and how you might go about designing an autonomous AI system. At the end of this course, you’ll be able to: • Describe the concept of machine teaching • Explain the role that SMEs play in training advanced AI • Evaluate the pros and cons of leveraging human expertise in the design of AI systems • Differentiate between automated and autonomous decision-making systems • Describe the limitations of automated systems and humans in real-time decision-making • Select use cases where autonomous AI will outperform both humans and automated systems • Propose an autonomous AI solution to a real-world problem • Validate your design against existing expertise and techniques for solving problems
Speaking to Inspire: Ceremonial and Motivational Speeches
University of Washington (via Coursera)
The most memorable speeches inspire, entertain, and praise. By blending stories and eloquence, great speeches highlight the core values motivating an audience. You might need to do this in a keynote address, a eulogy, or simply a business meeting. Inspiring audiences is a common, but difficult writing challenge. You want a speech that elevates the topic and the audience. This course gives you a method for preparing and delivering speeches that inspire and entertain. By the end of this course, you should be able to compose and deliver moving speeches that praise core audience values through evidence, storytelling, and humor. You should be able to write eloquent passages in tones appropriate to the audience and occasion and speak fluidly from either a well-prepared manuscript or from memory. Learners will record speeches, providing and receiving peer feedback.
مقدمة عن مخاطبة الجمهور - باللغة العربية
University of Washington (via Coursera)
تمنحك هذه الدورة التدريبية نموذجًا موثوقًا لإعداد العروض التقديمية الفعالة وتقديمها. في الأعمال التجارية وفي المدرسة وفي الحياة العامة، غالبًا ما يُطلب منا "إبداء بعض التعليقات". وفي كثير من الأحيان، يصبح الأشخاص المكلَّفون بإلقاء مثل هذه الخطابات مبلبلين، وقد لا يعرفون ما الذي يتحدثون عنه أو يبدؤون الحديث دون أن يكون لحديثهم معنى، أو قد لا يلقى حديثهم أي اهتمام من الجمهور. تم إعداد هذه الدورة لمساعدتك على التميز حيث يتعثر الآخرون. سنتعرّف على كيفية تنظيم المحادثات بوضوح وكتابتها بشكل يسهل تذكره وتقديمها بثقة. وفي نهاية الدورة، يجب أن تكون قادرًا على الحد بشكل كبير من خوفك من مخاطبة الجمهور واستخدام أساليب التمرن لتطوير صوت قوي وفعال ومرن وإلقاء الخطابات بحركات وإيماءات مرنة. إن نموذج الخطاب الذي سنتدرب عليه مفيد في الإحاطات الإعلامية والمحادثات الموجزة والمقابلات، وكذلك كأساس للعروض التقديمية التي تستغرق ساعة كاملة. إذا كنت مبتدئًا، فستساعدك هذه الدورة التدريبية على إتقان أساسيات الخطابة. وإذا كنت متحدثًا متمرسًا، فسوف تساعدك هذه الدورة على فهم مخاطبة الجمهور على نحو أفضل والانتقال إلى المستوى التالي.
Machine Learning: Clustering & Retrieval
University of Washington (via Coursera)
Case Studies: Finding Similar Documents A reader is interested in a specific news article and you want to find similar articles to recommend. What is the right notion of similarity? Moreover, what if there are millions of other documents? Each time you want to a retrieve a new document, do you need to search through all other documents? How do you group similar documents together? How do you discover new, emerging topics that the documents cover? In this third case study, finding similar documents, you will examine similarity-based algorithms for retrieval. In this course, you will also examine structured representations for describing the documents in the corpus, including clustering and mixed membership models, such as latent Dirichlet allocation (LDA). You will implement expectation maximization (EM) to learn the document clusterings, and see how to scale the methods using MapReduce. Learning Outcomes: By the end of this course, you will be able to: -Create a document retrieval system using k-nearest neighbors. -Identify various similarity metrics for text data. -Reduce computations in k-nearest neighbor search by using KD-trees. -Produce approximate nearest neighbors using locality sensitive hashing. -Compare and contrast supervised and unsupervised learning tasks. -Cluster documents by topic using k-means. -Describe how to parallelize k-means using MapReduce. -Examine probabilistic clustering approaches using mixtures models. -Fit a mixture of Gaussian model using expectation maximization (EM). -Perform mixed membership modeling using latent Dirichlet allocation (LDA). -Describe the steps of a Gibbs sampler and how to use its output to draw inferences. -Compare and contrast initialization techniques for non-convex optimization objectives. -Implement these techniques in Python.
Communicating Data Science Results
University of Washington (via Coursera)
Important note: The second assignment in this course covers the topic of Graph Analysis in the Cloud, in which you will use Elastic MapReduce and the Pig language to perform graph analysis over a moderately large dataset, about 600GB. In order to complete this assignment, you will need to make use of Amazon Web Services (AWS). Amazon has generously offered to provide up to $50 in free AWS credit to each learner in this course to allow you to complete the assignment. Further details regarding the process of receiving this credit are available in the welcome message for the course, as well as in the assignment itself. Please note that Amazon, University of Washington, and Coursera cannot reimburse you for any charges if you exhaust your credit. While we believe that this assignment contributes an excellent learning experience in this course, we understand that some learners may be unable or unwilling to use AWS. We are unable to issue Course Certificates for learners who do not complete the assignment that requires use of AWS. As such, you should not pay for a Course Certificate in Communicating Data Results if you are unable or unwilling to use AWS, as you will not be able to successfully complete the course without doing so. Making predictions is not enough! Effective data scientists know how to explain and interpret their results, and communicate findings accurately to stakeholders to inform business decisions. Visualization is the field of research in computer science that studies effective communication of quantitative results by linking perception, cognition, and algorithms to exploit the enormous bandwidth of the human visual cortex. In this course you will learn to recognize, design, and use effective visualizations. Just because you can make a prediction and convince others to act on it doesn’t mean you should. In this course you will explore the ethical considerations around big data and how these considerations are beginning to influence policy and p...
Practical Predictive Analytics: Models and Methods
University of Washington (via Coursera)
Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems. Learning Goals: After completing this course, you will be able to: 1. Design effective experiments and analyze the results 2. Use resampling methods to make clear and bulletproof statistical arguments without invoking esoteric notation 3. Explain and apply a core set of classification methods of increasing complexity (rules, trees, random forests), and associated optimization methods (gradient descent and variants) 4. Explain and apply a set of unsupervised learning concepts and methods 5. Describe the common idioms of large-scale graph analytics, including structural query, traversals and recursive queries, PageRank, and community detection
Data Manipulation at Scale: Systems and Algorithms
University of Washington (via Coursera)
Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales. In this course, you will learn the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against your requirements. You will learn how practical systems were derived from the frontier of research in computer science and what systems are coming on the horizon. Cloud computing, SQL and NoSQL databases, MapReduce and the ecosystem it spawned, Spark and its contemporaries, and specialized systems for graphs and arrays will be covered. You will also learn the history and context of data science, the skills, challenges, and methodologies the term implies, and how to structure a data science project. At the end of this course, you will be able to: Learning Goals: 1. Describe common patterns, challenges, and approaches associated with data science projects, and what makes them different from projects in related fields. 2. Identify and use the programming models associated with scalable data manipulation, including relational algebra, mapreduce, and other data flow models. 3. Use database technology adapted for large-scale analytics, including the concepts driving parallel databases, parallel query processing, and in-database analytics 4. Evaluate key-value stores and NoSQL systems, describe their tradeoffs with comparable systems, the details of important examples in the space, and future trends. 5. “Think” in MapReduce to effectively write algorithms for systems...
Lesson | Business English Skills: How to Write Effective Openings and Closings to Emails
University of Washington (via Coursera)
This lesson is part of a full course, Business English Networking. Take this lesson to get a short tutorial on the learning objectives covered. To dive deeper into this topic, take the full course. By the end of this lesson, you will be able to: Write effective sentences to begin an email Write friendly, closing sentences
Speaking to inform: Discussing complex ideas with clear explanations and dynamic slides
University of Washington (via Coursera)
In the professional realm, most speeches and presentations we give are informative in scope. A scientist needs to explain her recent research findings. A financial officer needs to report on quarterly earnings to his company’s board. A technology professional needs to educate a consumer about a new product. Any time you need to convey ideas or demonstrate a process, you’re dealing with informative speaking. Informative speaking is a fun puzzle. You need to think from the perspective of your audience to identify what they need to hear in order to understand the key ideas. How much does the audience already know? What are the most important elements to convey? How should one convey these ideas with appropriate breadth and depth given the time constraints of the speech? This demands a strategic approach to speech design that we’ll undertake in this class. By the end of the course, you should be able to explain complex ideas vividly and accessibly, design clear and compelling presentation slides, convey your passion for a topic while maintaining your professional credibility, and speak dynamically from notes and/or a manuscript. Learners will record speeches, providing and receiving peer feedback.