University of Pittsburgh
Public University • US
Showing 17 courses from University of Pittsburgh
Interactive, Geospatial & Narrative Data Visualization
University of Pittsburgh (via Coursera)
Elevate your data storytelling skills with "Interactive, Geospatial & Narrative Data Visualization" . This comprehensive program covers the essentials of visualizing data through interactive dashboards, geospatial analysis, and narrative visualization using Python and Tableau. Learn to design and implement interactive visualizations that improve user engagement and make complex data more accessible. Explore geospatial data to create compelling maps and understand spatial relationships. Dive into narrative visualization to craft engaging data stories that convey insights effectively. Master tools like Tableau and Python libraries (Matplotlib, Seaborn, Folium) to create various types of plots and advanced visualizations including maps with markers, choropleth maps, and network graphs. Engage in practical assignments and real-world projects that challenge you to develop, analyze, and optimize data visualizations. By the end of this course, you will have the expertise to build stunning visualizations, interpret complex datasets, and tell impactful data stories.
Distributed Systems and Web Services
University of Pittsburgh (via Coursera)
Develop the technical foundation to design and implement scalable, interconnected cloud systems. In this course, you’ll explore distributed architectures and web service design that power today’s high-performance applications. Through hands-on lessons, you’ll learn how distributed systems manage computation, storage, and communication across multiple machines, and how RESTful APIs enable seamless data exchange between services. You’ll also gain experience deploying applications using virtualization and cloud storage technologies. By the end of the course, you’ll be able to analyze distributed architectures, build and test web services using Flask, and apply containerization concepts with Docker. You’ll understand how cloud components integrate to create flexible, reliable, and scalable systems. Designed for learners seeking to expand their cloud development and systems engineering skills, this course bridges theory and practice through real-world use cases and guided coding exercises, preparing you for advanced studies or roles in cloud computing, backend development, or systems design.
Mainstream Smart Home Technology as Assistive Technology
University of Pittsburgh (via Coursera)
This course aims to provide healthcare providers, social service professionals, and caregivers with a comprehensive understanding of smart home technology and how it can be utilized as assistive technology to improve the well-being, independence, and participation for older adults and individuals with disabilities. Students will learn about the different components of a smart home, including the input methods, smart home controllers, and smart home devices. The course will cover major smart home ecosystems, such as Amazon Alexa, Google Home, Apple Home, along with common wireless communication protocols, such as Z-wave, Zigbee, Bluetooth, Wi-Fi, and Thread. The smart home standard Matter will also be introduced.
Cloud Computing Fundamentals
University of Pittsburgh (via Coursera)
Master the essential concepts and hands-on skills needed to understand cloud computing from multiple perspectives. This comprehensive course takes you from cloud computing history and definitions through advanced database technologies, providing both theoretical foundations and practical implementation experience. You'll explore how cloud platforms have transformed modern technology, learning to evaluate IaaS, PaaS, and SaaS service models while gaining hands-on experience with virtualization using VirtualBox. The course progresses through cloud data infrastructure, where you'll differentiate between databases, data warehouses, and data lakes, and learn to apply de-normalized schemas like Star and Snowflake for optimal performance. By course completion, you'll confidently compare and select appropriate database technologies—MySQL, MongoDB, and Neo4j—understanding ACID versus BASE properties and horizontal versus vertical scaling strategies. What sets this course apart is its balanced approach: combining historical context, architectural understanding, and practical coding exercises using Python, GitHub, and Flask. Whether you're transitioning into cloud roles or expanding your technical expertise, this course equips you with the foundational knowledge and practical skills essential for modern cloud computing careers.
Clinical Terminology for International and U.S. Students
University of Pittsburgh (via Coursera)
Understanding the clinical terms and abbreviations commonly used during verbal or written communication in U.S. hospitals is challenging. This course is designed for U.S. health care profession students and for international students and practitioners who want to become more familiar with the language of the U.S. clinical setting. Others, such as caregivers and medical interpreters, who wish to develop a better understanding of terms and abbreviations used by health care providers will find this course helpful. The course provides visual and auditory learning experiences to enhance the understanding of terms and abbreviations commonly encountered on a general U.S. hospital unit. You need to pay the fee or apply for financial aid to access the course and earn a certificate. To find out more, click Learn more and apply next to the information about Financial Aid. (Use a computer, not a mobile device, for this step.)
Probability Theory and Regression for Predictive Analytics
University of Pittsburgh (via Coursera)
Transform your data science capabilities with the "Probability Theory and Regression for Predictive Analytics" course. This program is designed to provide essential mathematical and statistical skills necessary for predictive modeling and data analysis. Dive into probability concepts, including conditional probability, Bayes’ Theorem, and various probability distributions. Further, apply regression techniques to enhance your ability to predict and interpret data trends. Begin by understanding and calculating conditional probabilities and learning Bayes’ Theorem for probabilistic inference. Explore different probability distributions such as Bernoulli, Binomial, Geometric, Poisson, and Normal distributions, which are fundamental for modeling and analyzing data. Advance to ordinary least squares (OLS) regression, applying matrix transposition and probabilistic techniques to fit linear models to data. Gain a deeper understanding of regression analysis methodologies, from basics to advanced topics, including multicollinearity, interaction effects, Lasso regression, and logistic regression. Engage in practical assignments and real-world projects to apply probability theory and regression techniques, using Python as a powerful tool for statistics and predictive analytics. By the end of this course, you'll be equipped with a solid foundation to tackle advanced data science topics confidently.
Introduction to Dental Terminology
University of Pittsburgh (via Coursera)
This course provides foundational knowledge for those interested in developing a better understanding of basic dental terminology. The course will define and explore clinical and non-clinical terms commonly used in endodontics, oral and maxillofacial surgery, orthodontics, pediatric dentistry, periodontics, prosthodontics, restorative dentistry, dental radiography, and dental practice administration. The course is organized by specialty so participants may personalize their experience and focus their learning as needed. Identifying and applying these terms will help the learner to become a better communicator and more effective oral healthcare team member, to prepare for future studies, and to act as a more informed oral health advocate for themselves or others.
Big Data Processing with Hadoop and Spark
University of Pittsburgh (via Coursera)
Master the tools and techniques that power large-scale data processing and analytics. This course introduces the principles and frameworks of Big Data Processing with Hadoop and Spark, enabling learners to manage, process, and analyze massive datasets efficiently. You’ll start by understanding the Hadoop ecosystem, including HDFS and MapReduce, and how distributed storage and computation work together to handle data at scale. Then, you’ll explore Apache Spark, a powerful framework for fast, in-memory data processing and real-time analytics. Through guided exercises and case studies, you’ll learn how to build scalable data pipelines, optimize performance, and apply transformations for business insights. By the end of this course, you’ll be equipped to handle complex data workloads using industry-standard big data tools. Ideal for aspiring data engineers, analysts, and developers, this course bridges data management and cloud computing—preparing you to design, implement, and manage big data solutions that drive intelligent decision-making in modern organizations.
Linear Algebra and Regression Fundamentals for Data Science
University of Pittsburgh (via Coursera)
Unlock essential mathematical skills with "Linear Algebra and Regression Fundamentals for Data Science" , which sets the foundation for advanced data science studies. This comprehensive program emphasizes practical application over theoretical concepts, ensuring you gain hands-on experience with Python and its powerful libraries. Begin by mastering linear algebra concepts, where you'll learn to perform vector arithmetic and matrix operations, and calculate eigenvectors and eigenvalues using NumPy. Understand how these principles are crucial for data science tasks, from data manipulation to complex computations involving large datasets. Progress to solving systems of linear equations with backsolving techniques and matrix inversion, utilizing Python’s Pandas package for efficient data handling. Explore how these methods are applied in real-world scenarios, ensuring a practical understanding of linear systems and their significance in data analysis. Advance your skills with ordinary least squares (OLS) regression, learning to fit linear models to data using probabilistic techniques and matrix transposition. The course will guide you through using regression analysis to interpret and predict data trends, making it a vital tool for any data scientist. Through practical assignments and real-world projects, you will apply linear algebra and regression techniques to solve complex problems, visualize data, and draw meaningful insights. By the end of this course, you will possess a solid foundation in the essential mathematical skills required for advanced data science, empowering you to leverage Python for effective data analysis and decision-making.
Tableau, Networks & Time Series Data Visualization
University of Pittsburgh (via Coursera)
Unlock the power of data with "Tableau, Networks & Time Series Data Visualization" . This comprehensive program is designed to teach you the essentials of data storytelling through visualizations using Python and Tableau. Starting with the basics of Tableau, you'll learn to create and customize various visualizations, build interactive dashboards, and conduct detailed analytics. Dive into network visualization to understand and depict complex networks and connected data. Using Python libraries, you will create and customize network visualizations that highlight relationships and structures within data. Explore time series data visualization to interpret and present data over time. You’ll master techniques for loading, preparing, and visualizing time series data using Python, enhancing your ability to forecast and analyze trends effectively. By the end of this course, you will have the skills needed to create compelling, insightful, and interactive data visualizations, making complex data more understandable and actionable.
Law You Can Use
University of Pittsburgh (via Coursera)
This course introduces relevant legal topics through flexible weekly modules, allowing completion within five weeks or less. Each standalone module is designed to be completed independently, so you can engage with all five modules or focus on the ones most relevant to your needs. Topics covered include an overview of the U.S. legal system, healthcare compliance with a focus on HIPAA regulations, human resources law addressing issues like disability discrimination and workplace policies, corporate compliance exploring ethics and emerging trends, and international business law covering dispute resolution and enforcing judgments across borders.
Gender and Sexuality: Diversity and Inclusion in the Workplace
University of Pittsburgh (via Coursera)
What is sex? What is gender? What is sexuality? What do we mean by LGBTQIA? How are these concepts related to the workplace? How have our understandings of these terms changed over time, and how have these changes impacted work and culture? To help you answer these important questions, this course will introduce you to the exciting field of gender, sexuality, and women's studies, and to LGBTQIA identities. We will use a range of interdisciplinary concepts, tools, and methods to understand and analyze how identity shapes our experiences in culture and in the workplace. Because we all live with gender expectations, this course is crucial for any profession, and for understanding the world around us. Also, you will learn key concepts that will help you to interpret and understand the world we share.
idea 2 IMPACT: An Introduction to Translating Assistive Health Technologies and Other Products
University of Pittsburgh (via Coursera)
idea 2 IMPACT (i2I) is an online, 6-week course that will guide you step by step through the experience of developing an innovative and entrepreneurial idea in the area of assistive technology (AT). Each week, you will focus on a stage of the translational process as you work in teams to identify a problem, analyze stakeholders, define a solution, describe its benefits, research the competition, articulate differentiators, and create an action plan.
Statistics and Calculus Methods for Data Analysis
University of Pittsburgh (via Coursera)
This program focuses on the practical application of essential mathematical, statistical, and analytical techniques vital for advanced data science studies. Learn to calculate expected values, understand the normal distribution, perform derivative calculations, and solve complex integrals, all demonstrated with Python. Start with the concept of expected values and explore their relationship to the normal distribution, laying the groundwork for statistical analysis and predictive modeling. Move on to calculus, mastering derivatives and their applications in tasks like optimization and rate of change analysis. Advance further into solving integrals, including techniques for handling complex integrations and their significance in continuous data analysis. By the end of the course, you will possess a strong mathematical foundation to tackle more advanced data science topics. Engage in practical assignments and real-world projects to apply these methods in solving complex data problems. By leveraging tools like Python, you will gain hands-on understanding of these critical concepts.
Data Visualization Fundamentals in Python
University of Pittsburgh (via Coursera)
The "Data Visualization Fundamentals in Python" course empowers you to transform data into compelling visual narratives. Dive into the principles and best practices of data visualization, blending the art and science to tell impactful data stories using Python. Through this course, you will master creating basic and advanced data visualizations and learn to effectively communicate complex information visually. You will explore Python libraries such as Matplotlib and Seaborn and understand how to customize visual elements to create clear, insightful, and visually appealing data representations. You will develop skills to apply fundamental principles, incorporate human perception aspects, customize your plots, and create interactive visualizations ensuring an accurate interpretation of data. This course will equip you with techniques for transforming complex datasets into coherent visuals, optimizing your ability to convey data-driven insights effectively.
Disaster Preparedness
University of Pittsburgh (via Coursera)
Have you ever viewed a news report depicting the aftermath of a devastating natural disaster? The damage to human life and property are both staggering and heartbreaking. All parts of the world face the possibility of floods, hurricanes, tornados, fires, landslides, earthquakes, tsunamis, and other natural phenomena. Are you prepared if disaster would strike you? This course will help you prepare! The course is appropriate for any learner who is proactive about developing the core competencies of disaster readiness and survival planning. It is especially useful if you are seeking techniques that can ensure your personal protection, as well as the safety of your family, property, and belongings, during a natural disaster. In addition, it offers essential preparation for a variety of emergency situations and inconveniences, even if you do not live in major tornado, flood, hurricane, tsunami, or earthquake zone. For instance, could you and your loved ones manage without access to potable water, electricity, fuel, and banking facilities? If you are unsure of your ability to respond in any of these possible scenarios, this course is for you! Throughout the course, you will be introduced to the Disaster Cycle, specifically the Mitigation and Recovery phases, and will create an extensive personal preparedness plan for survival in the absence of common amenities, such as food and water, shelter, and communication. You will also acquire practical, easy-to-apply strategies for maintaining a healthy attitude during disaster which can allow you to remain calm, avoid panic, and draw upon inner and outer resources in dire circumstances. Although death may be an inevitable outcome of extreme circumstances, a balanced outlook can provide comfort for all parties involved. Finally, issues of how institutions and governments can aid in disaster are also discussed. If you are interested in this topic you may be interested in other online programs at the University of Pittsburgh Schoo...
Disability Awareness and Support
University of Pittsburgh (via Coursera)
The goal of this course is to promote equal opportunity and the full participation of students with disabilities in higher education by helping participants advance their awareness of the meaning of accessibility in education. Participants will gain competence and confidence in working with students by focusing on legislation, universal design, and assistive technologies. Thank you to Abbas (Bobby) Husain Quamar, Graduate Student Researcher in the Department of Rehabilitation Science and Technology at the University of Pittsburgh, for his contributions to the course.