500 Free Computer Science Courses from the World’s Top CS Universities

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500 Free Computer Science Courses from the World’s Top CS Universities

Manoel Cortes Mendez

Developer and writer at Class Central

Every year, Class Central publishes rankings of the world’s highest rated and most popular online courses.

These rankings are based on user ratings and total enrollments. You can see the full annual course ratings here.

But in this article, I'm going to adopt a different approach. Instead of just showing the top courses, I'll show you which universities seem to have the best courses overall, then show you all the free online courses those universities offer for studying computer science.

Methodology

I started with the three leading global university rankings and looked at the latest editions of their computer science rankings:

• QS: World University Rankings 2020 — Computer Science & Information Systems
• Times Higher Education: World University Rankings 2020 — Computer Science
• Shanghai Ranking Consultancy: Academic Ranking of World Universities 2019 — Computer Science & Engineering

My approach was simple. First, I combined the three rankings into one by averaging each university’s position across the three rankings.

Second, I limited the list to the top-fifty institutions that offer computer science courses online.

Third, I leveraged Class Central’s database to build a list of those courses.

Combining rankings in Jupyter Notebook

As you can see above, the three institutions that topped the combined ranking were #1 MIT, #2 Stanford, and #3 Carnegie Mellon. If you’d like to see the data and the process I followed to get to that result, check out my GitHub repo.

After compiling each university’s offering, the end result is a list of 500 online courses offered by the 2020 world 50 best universities for studying computer science.

Notable Courses

Unsurprisingly, some of the courses in the list are also part of Class Central’s best online courses of all time. You can find these below. They’re all great options, especially for novice e-learners, since they exemplify the best that online education has to offer.

• Programming for Everybody (Getting Started with Python) from University of Michigan ★★★★★(9662)
• Machine Learning from Stanford University ★★★★★(358)
• Introduction to Computer Science and Programming Using Python from Massachusetts Institute of Technology ★★★★☆(122)
• Learn to Program: The Fundamentals from University of Toronto ★★★★★(105)
• CS50's Introduction to Computer Science from Harvard University ★★★★★(84)
• The Analytics Edge from Massachusetts Institute of Technology ★★★★★(79)
• Python and Statistics for Financial Analysis from The Hong Kong University of Science and Technology ★★★★☆(71)
• Computing in Python I: Fundamentals and Procedural Programming from Georgia Institute of Technology ★★★★★(69)
• Divide and Conquer, Sorting and Searching, and Randomized Algorithms from Stanford University ★★★★★(68)
• Functional Programming Principles in Scala from École Polytechnique Fédérale de Lausanne ★★★★★(66)
• Cryptography I from Stanford University ★★★★★(51)
• Python for Data Science from University of California, San Diego ★★★★☆(43)
• Introduction to HTML5 from University of Michigan ★★★★☆(42)
• Internet History, Technology, and Security from University of Michigan ★★★★★(39)

Full Course List

The full list is split into subjects. Click on one to jump to the relevant courses. Courses that are also in Class Central's all-time top-100 ranking are denoted with a star (⭐).

• AI & Machine Learning (65 courses)
• Algorithms & Data Structures (60 courses)
• Bioinformatics & Healthcare (30 courses)
• Computer Science (90 courses)
• Cybersecurity (22 courses)
• Data Science (109 courses)
• Programming Languages (60 courses)
• Software Development (57 courses)
• Quantum Computing (7 courses)

With 500 courses to choose from, I hope you find something you like. But if those aren’t enough, check out Class Central’s catalog of over 15,000 online courses.

AI & Machine Learning — 65 Courses

• Machine Learning from Stanford University ★★★★★(358) ⭐
• Machine Learning Foundations: A Case Study Approach from University of Washington ★★★★☆(38)
• CS188.1x: Artificial Intelligence from University of California, Berkeley ★★★★★(31)
• Practical Machine Learning from Johns Hopkins University ★★★☆☆(26)
• Introduction to Artificial Intelligence from Stanford University ★★★★☆(24)
• Artificial Intelligence for Robotics from Stanford University ★★★★★(23)
• Introduction to Machine Learning Course from Stanford University ★★★★☆(19)
• Machine Learning: Regression from University of Washington ★★★★★(19)
• Probabilistic Graphical Models 1: Representation from Stanford University ★★★★☆(18)
• Neural Networks and Deep Learning from deeplearning.ai ★★★★★(15)
• Machine Learning for Data Science and Analytics from Columbia University ★★★☆☆(15)
• Machine Learning With Big Data from University of California, San Diego ★★☆☆☆(13)
• Artificial Intelligence (AI) from Columbia University ★★★★☆(10)
• Machine Learning from Columbia University ★★★★☆(10)
• Learning from Data (Introductory Machine Learning course) from California Institute of Technology ★★★★★(10)
• Mathematics for Machine Learning: Multivariate Calculus from Imperial College London ★★★★★(9)
• Reinforcement Learning from Brown University ★★★☆☆(8)
• Machine Learning: Classification from University of Washington ★★★★★(8)
• Convolutional Neural Networks from deeplearning.ai ★★★★★(8)
• Guided Tour of Machine Learning in Finance from New York University (NYU) ★☆☆☆☆(7)
• Introduction to Computer Vision from Georgia Institute of Technology ★★★★★(7)
• Machine Learning from Georgia Institute of Technology ★★★★☆(6)
• Applied Machine Learning in Python from University of Michigan ★★★★☆(4)
• Machine Learning: Clustering & Retrieval from University of Washington ★★★★★(4)
• Sequence Models from deeplearning.ai ★★★★★(4)
• Structuring Machine Learning Projects from deeplearning.ai ★★★★★(3)
• Probabilistic Graphical Models 2: Inference from Stanford University ★★★★☆(3)
• Autonomous Mobile Robots from ETH Zurich ★★★☆☆(3)
• Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization from deeplearning.ai ★★★★★(3)
• Machine Learning: Unsupervised Learning from Brown University ★★★☆☆(3)
• Machine Learning Fundamentals from University of California, San Diego ★★★★☆(3)
• Practical Predictive Analytics: Models and Methods from University of Washington ★★☆☆☆(3)
• Mathematics for Machine Learning: PCA from Imperial College London ★★☆☆☆(3)
• Robotics: Perception from University of Pennsylvania ★★★☆☆(3)
• Knowledge-Based AI: Cognitive Systems from Georgia Institute of Technology ★★★☆☆(2)
• Reinforcement Learning in Finance from New York University (NYU) ★☆☆☆☆(2)
• 6.S094: Deep Learning for Self-Driving Cars from Massachusetts Institute of Technology ★★★★☆(2)
• 6.S191: Introduction to Deep Learning from Massachusetts Institute of Technology ★★★★☆(2)
• Applied Text Mining in Python from University of Michigan ★★☆☆☆(2)
• Overview of Advanced Methods of Reinforcement Learning in Finance from New York University (NYU) ★☆☆☆☆(1)
• Fundamentals of Machine Learning in Finance from New York University (NYU) ★☆☆☆☆(1)
• Deep Learning for Natural Language Processing from University of Oxford ★★★★★(1)
• Introduction to Self-Driving Cars from University of Toronto
• State Estimation and Localization for Self-Driving Cars from University of Toronto
• Motion Planning for Self-Driving Cars from University of Toronto
• Visual Perception for Self-Driving Cars from University of Toronto
• [New] Robotics: Vision Intelligence and Machine Learning from University of Pennsylvania
• Python Project: pillow, tesseract, and opencv from University of Michigan
• [New] Getting started with TensorFlow 2 from Imperial College London
• [New] CS50's Introduction to Artificial Intelligence with Python from Harvard University
• Probabilistic Graphical Models 3: Learning from Stanford University
• Innovations in Investment Technology: Artificial Intelligence from University of Michigan
• Artificial Intelligence from Georgia Institute of Technology
• FA18: Machine Learning from Georgia Institute of Technology
• 计算机辅助翻译原理与实践 Principles and Practice of Computer-Aided Translation from Peking University
• Machine Learning with Python-From Linear Models to Deep Learning from Massachusetts Institute of Technology
• Foundations of Data Science: Prediction and Machine Learning from University of California, Berkeley
• Design Thinking and Predictive Analytics for Data Products from University of California, San Diego
• Deploying Machine Learning Models from University of California, San Diego
• FA17: Machine Learning from Georgia Institute of Technology
• Machine Learning for Accounting with Python from University of Illinois at Urbana-Champaign
• Data Analytics Foundations for Accountancy II from University of Illinois at Urbana-Champaign
• Machine Learning from The University of Texas at Austin
• 大数据机器学习|Big Data Machine Learning from Tsinghua University
• Statistical Machine Learning from Carnegie Mellon University

Algorithms & Data Structures — 60 Courses

• Divide and Conquer, Sorting and Searching, and Randomized Algorithms from Stanford University ★★★★★(68) ⭐
• Algorithms, Part I from Princeton University ★★★★★(60)
• Algorithmic Toolbox from University of California, San Diego ★★★★☆(23)
• Algorithms, Part II from Princeton University ★★★★★(21)
• Automata Theory from Stanford University ★★★★☆(20)
• Text Retrieval and Search Engines from University of Illinois at Urbana-Champaign ★★★☆☆(14)
• Design of Computer Programs from Stanford University ★★★★☆(13)
• How to Code: Simple Data from The University of British Columbia ★★★★☆(12)
• Data Structures from University of California, San Diego ★★★★☆(8)
• Data Structures and Performance from University of California, San Diego ★★★★☆(6)
• Data Structures: An Active Learning Approach from University of California, San Diego ★★★★★(5)
• Computation Structures 1: Digital Circuits from Massachusetts Institute of Technology ★★★★☆(5)
• Algorithms on Strings from University of California, San Diego ★★★☆☆(4)
• Analysis of Algorithms from Princeton University ★★★★★(4)
• Programming Languages, Part B from University of Washington ★★★★☆(3)
• Algorithms on Graphs from University of California, San Diego ★★★★☆(2)
• The Beauty and Joy of Computing - AP® CS Principles Part 1 from University of California, Berkeley ★★★★★(2)
• Algorithmic Design and Techniques from University of California, San Diego ★★★☆☆(2)
• Programming Languages, Part C from University of Washington ★★★★☆(2)
• How to Code: Complex Data from The University of British Columbia ★★★★★(2)
• Computation Structures 2: Computer Architecture from Massachusetts Institute of Technology ★★★★☆(1)
• Algorithm Design and Analysis from University of Pennsylvania ★★★★☆(1)
• Advanced Algorithms and Complexity from University of California, San Diego ★★★☆☆(1)
• Computability, Complexity & Algorithms from Georgia Institute of Technology ★★★★★(1)
• 数据结构与算法设计(下) | Data Structures and Algorithm Design Part II from Tsinghua University ★★★★★(1)
• Algorithms: Design and Analysis, Part 1 from Stanford University
• Graph Search, Shortest Paths, and Data Structures from Stanford University
• Algorithms: Design and Analysis, Part 2 from Stanford University
• Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming from Stanford University
• Shortest Paths Revisited, NP-Complete Problems and What To Do About Them from Stanford University
• Computation Structures 3: Computer Organization from Massachusetts Institute of Technology
• Data Structures and Software Design from University of Pennsylvania
• The Beauty and Joy of Computing (CS Principles), Part 4 from University of California, Berkeley
• The Beauty and Joy of Computing (CS Principles), Part 1 from University of California, Berkeley
• The Beauty and Joy of Computing (CS Principles), Part 3 from University of California, Berkeley
• The Beauty and Joy of Computing - AP® CS Principles Part 2 from University of California, Berkeley
• Data Structures Fundamentals from University of California, San Diego
• Graph Algorithms from University of California, San Diego
• String Processing and Pattern Matching Algorithms from University of California, San Diego
• NP-Complete Problems from University of California, San Diego
• Introduction to Graduate Algorithms from Georgia Institute of Technology
• High Performance Computing from Georgia Institute of Technology
• Computer Science: Algorithms, Theory, and Machines from Princeton University
• Unordered Data Structures from University of Illinois at Urbana-Champaign
• Object-Oriented Data Structures in C++ from University of Illinois at Urbana-Champaign
• Ordered Data Structures from University of Illinois at Urbana-Champaign
• 离散优化算法篇 Solving Algorithms for Discrete Optimization from The Chinese University of Hong Kong
• Solving Algorithms for Discrete Optimization from University of Melbourne
• Advanced Modeling for Discrete Optimization from University of Melbourne
• Basic Modeling for Discrete Optimization from University of Melbourne
• Data Structures and Algorithms, Part 2 from Peking University
• 数据结构与算法(A) part 1 from Peking University
• 算法设计与分析 Design and Analysis of Algorithms from Peking University
• Advanced Design and Analysis of Algorithms 算法设计与分析(高级) from Peking University
• 算法基础 from Peking University
• 算法基础 Fundamental Algorithms from Peking University
• 高级数据结构与算法 from Peking University
• Introduction to Theoretical Computer Science 理论计算机科学基础 from Peking University
• 数据结构与算法设计(上) | Data Structures and Algorithm Design Part I from Tsinghua University
• Discrete Mathematics from Shanghai Jiao Tong University

Bioinformatics & Healthcare — 30 Courses

• Finding Hidden Messages in DNA (Bioinformatics I) from University of California, San Diego ★★★★★(17)
• DCO042 - Python For Informatics from University of Michigan ★★★★★(14)
• Python for Genomic Data Science from Johns Hopkins University ★★☆☆☆(12)
• Biology Meets Programming: Bioinformatics for Beginners from University of California, San Diego ★★★★☆(8)
• Genome Sequencing (Bioinformatics II) from University of California, San Diego ★★★★★(4)
• Quantitative Biology Workshop from Massachusetts Institute of Technology ★★★★★(2)
• Comparing Genes, Proteins, and Genomes (Bioinformatics III) from University of California, San Diego ★★★★★(2)
• Genomic Data Science and Clustering (Bioinformatics V) from University of California, San Diego ★★★★☆(2)
• HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Clinical Perspective) from Columbia University ★☆☆☆☆(1)
• HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Administrative/IT Perspective) from Columbia University ★★★★★(1)
• Health Informatics in the Cloud from Georgia Institute of Technology ★★★★☆(1)
• Dynamic Programming: Applications In Machine Learning and Genomics from University of California, San Diego
• Algorithms and Data Structures Capstone from University of California, San Diego
• Introduction to Genomic Data Science from University of California, San Diego
• Graph Algorithms in Genome Sequencing from University of California, San Diego
• Finding Mutations in DNA and Proteins (Bioinformatics VI) from University of California, San Diego
• Molecular Evolution (Bioinformatics IV) from University of California, San Diego
• Plant Bioinformatics Capstone from University of Toronto
• Plant Bioinformatics from University of Toronto
• Bioinformatics: Introduction and Methods 生物信息学: 导论与方法 from Peking University
• 生物信息学: 导论与方法 from Peking University
• Global Health Informatics to Improve Quality of Care from Massachusetts Institute of Technology
• Leading Change in Health Informatics from Johns Hopkins University
• The Social and Technical Context of Health Informatics from Johns Hopkins University
• The Data Science of Health Informatics from Johns Hopkins University
• The Outcomes and Interventions of Health Informatics from Johns Hopkins University
• HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Social/Peer Perspective) from Columbia University
• Health Informatics: A Current and Historical Perspective from Georgia Institute of Technology
• Health Informatics: The Cutting Edge from Georgia Institute of Technology
• Health Informatics: Data and Interoperability Standards from Georgia Institute of Technology

Computer Science — 90 Courses

• Using Databases with Python from University of Michigan ★★★★★(1570)
• Introduction to Computer Science and Programming Using Python from Massachusetts Institute of Technology ★★★★☆(122) ⭐
• CS50's Introduction to Computer Science from Harvard University ★★★★★(84) ⭐
• Functional Programming Principles in Scala from École Polytechnique Fédérale de Lausanne ★★★★★(66) ⭐
• Internet History, Technology, and Security from University of Michigan ★★★★★(39) ⭐
• Computer Science 101 from Stanford University ★★★★☆(17)
• Introduction to Computer Networking from Stanford University ★★★★★(12)
• Hardware Security from University of Maryland, College Park ★★★☆☆(11)
• Usable Security from University of Maryland, College Park ★★★☆☆(9)
• Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure from University of Illinois at Urbana-Champaign ★★★☆☆(8)
• Software Defined Networking from Princeton University ★★★★☆(7)
• Computer Graphics from University of California, San Diego ★★★★☆(6)
• Computer Architecture from Princeton University ★★★★☆(6)
• Internet of Things: How did we get here? from University of California, San Diego ★★☆☆☆(6)
• Ruby on Rails Web Services and Integration with MongoDB from Johns Hopkins University ★★★★★(6)
• Computer Networking from Georgia Institute of Technology ★★★★☆(6)
• Enabling Technologies for Data Science and Analytics: The Internet of Things from Columbia University ★☆☆☆☆(5)
• Software Construction in Java from Massachusetts Institute of Technology ★★★★★(5)
• Advanced Operating Systems from Georgia Institute of Technology ★★★★★(5)
• Animation and CGI Motion from Columbia University ★★★★☆(4)
• Introduction to Computer Architecture from Carnegie Mellon University ★★★★★(4)
• Rails with Active Record and Action Pack from Johns Hopkins University ★★★★☆(4)
• Internet of Things: Setting Up Your DragonBoard™ Development Platform from University of California, San Diego ★★★☆☆(4)
• Internet of Things: Communication Technologies from University of California, San Diego ★★★☆☆(3)
• Introduction to Computing using Python from Georgia Institute of Technology ★★★★★(3)
• Networks Illustrated: Principles without Calculus from Princeton University ★★★★☆(3)
• Computational Probability and Inference from Massachusetts Institute of Technology ★★★★☆(3)
• Compilers from Stanford University ★★★★☆(2)
• Advanced Data Structures in Java from University of California, San Diego ★★★★☆(2)
• Software Architecture & Design from Georgia Institute of Technology ★★★★★(2)
• Introduction to Operating Systems from Georgia Institute of Technology ★★★★★(2)
• Networks: Friends, Money, and Bytes from Princeton University ★★★★☆(2)
• Software Development Capstone Project from The University of British Columbia ★☆☆☆☆(2)
• The Unix Workbench from Johns Hopkins University ★★★★☆(2)
• CS50's AP® Computer Science Principles from Harvard University ★★★★★(1)
• CS50's Understanding Technology from Harvard University ★★★★★(1)
• CS50's Computer Science for Business Professionals from Harvard University ★★★★★(1)
• Computational Thinking for Modeling and Simulation from Massachusetts Institute of Technology ★★☆☆☆(1)
• High Performance Computer Architecture from Georgia Institute of Technology ★★★★★(1)
• Computational Photography from Georgia Institute of Technology ★★★★☆(1)
• Software Engineering: Introduction from The University of British Columbia ★★★★★(1)
• Software Construction: Object-Oriented Design from The University of British Columbia ★★☆☆☆(1)
• Software Construction: Data Abstraction from The University of British Columbia ★★★☆☆(1)
• Nature, in Code: Biology in JavaScript from École Polytechnique Fédérale de Lausanne ★★★☆☆(1)
• Computing: Art, Magic, Science from ETH Zurich ★★★★☆(1)
• Introduction to Structured Query Language (SQL) from University of Michigan ★★★★★(1)
• Database Systems Concepts & Design from Georgia Institute of Technology ★★★★☆(1)
• Database Systems Concepts and Design from Georgia Institute of Technology
• Embedded Systems from Georgia Institute of Technology
• CS50 for Lawyers from Harvard University
• Principles of Computing from Stanford University
• Hacker Tools from Massachusetts Institute of Technology
• Advanced Software Construction in Java from Massachusetts Institute of Technology
• Computational Thinking for Problem Solving from University of Pennsylvania
• Compilers: Theory and Practice from Georgia Institute of Technology
• Human-Computer Interaction I: Fundamentals & Design Principles from Georgia Institute of Technology
• Accessible Gamification from Georgia Institute of Technology
• Human-Computer Interaction II: Cognition, Context & Culture from Georgia Institute of Technology
• Human-Computer Interaction III: Ethics, Needfinding & Prototyping from Georgia Institute of Technology
• GT - Refresher - Advanced OS from Georgia Institute of Technology
• Human-Computer Interaction IV: Evaluation, Agile Methods & Beyond from Georgia Institute of Technology
• Computer Science: Programming with a Purpose from Princeton University
• 离散优化建模基础篇 Basic Modeling for Discrete Optimization from The Chinese University of Hong Kong
• 离散优化建模高阶篇 Advanced Modeling for Discrete Optimization from The Chinese University of Hong Kong
• 操作系统与虚拟化安全 from Peking University
• 操作系统原理（Operating Systems） from Peking University
• 计算机组成 Computer Organization from Peking University
• 数据结构基础 from Peking University
• LAFF-On Programming for High Performance from The University of Texas at Austin
• LAFF – On Programming for Correctness from The University of Texas at Austin
• 计算几何 | Computational Geometry from Tsinghua University
• [New] Generative Modelling from National University of Singapore
• [New] Performative Modelling from National University of Singapore
• Procedural Modelling from National University of Singapore
• Basics of Computing and Programming from New York University (NYU)
• Computer Hardware and Operating Systems from New York University (NYU)
• Computing: Art, Magic, Science - Part II from ETH Zurich
• Internet of Things V2: Setting up and Using Cloud Services from University of California, San Diego
• Internet of Things: Sensing and Actuation From Devices from University of California, San Diego
• Internet of Things: Sensing and Actuation From Devices from University of California, San Diego
• Internet of Things V2: DragonBoard™ bring up and community ecosystem from University of California, San Diego
• Internet of Things: Multimedia Technologies from University of California, San Diego
• Cyber-Physical Systems Design & Analysis from Georgia Institute of Technology
• Information and Communication Technology (ICT) Accessibility from Georgia Institute of Technology
• Portfolio Management, Governance, & the PMO from University of Washington
• Leadership and Management for PM Practitioners in IT from University of Washington
• Information Systems Auditing, Controls and Assurance from The Hong Kong University of Science and Technology
• Сетевое администрирование: от теории к практике from Tsinghua University
• Introduction to Networking from New York University (NYU)
• iLabX – The Internet Masterclass from Technische Universität München (Technical University of Munich)

Cybersecurity — 22 Courses

• Cryptography I from Stanford University ★★★★★(51) ⭐
• Software Security from University of Maryland, College Park ★★★★☆(27)
• Bitcoin and Cryptocurrency Technologies from Princeton University ★★★★☆(18)
• Cryptography from University of Maryland, College Park ★★★★☆(8)
• Intro to Information Security from Georgia Institute of Technology ★★☆☆☆(2)
• Bitcoin and Cryptocurrencies from University of California, Berkeley ★★★★★(1)
• Cyber-Physical Systems Security from Georgia Institute of Technology
• Finding Your Cybersecurity Career Path from University of Washington
• Building a Cybersecurity Toolkit from University of Washington
• Cybersecurity: The CISO's View from University of Washington
• Introduction to Cybersecurity from University of Washington
• Cyber Attack Countermeasures from New York University (NYU)
• Introduction to Cyber Attacks from New York University (NYU)
• Enterprise and Infrastructure Security from New York University (NYU)
• Cryptocurrency and Blockchain: An Introduction to Digital Currencies from University of Pennsylvania
• Cryptocurrency and Blockchain Technology Explained from University of Michigan
• Blockchain and Cryptocurrency Explained from University of Michigan
• Blockchain Technology from University of California, Berkeley
• Number Theory and Cryptography from University of California, San Diego
• Quantum Cryptography from California Institute of Technology
• Network Security from Georgia Institute of Technology
• Real-Time Cyber Threat Detection and Mitigation from New York University (NYU)

Data Science — 109 Courses

• R Programming from Johns Hopkins University ★★★☆☆(241)
• The Data Scientist’s Toolbox from Johns Hopkins University ★★★☆☆(162)
• The Analytics Edge from Massachusetts Institute of Technology ★★★★★(79) ⭐
• Getting and Cleaning Data from Johns Hopkins University ★★★☆☆(56)
• Introduction to Data Science in Python from University of Michigan ★★☆☆☆(44)
• Python for Data Science from University of California, San Diego ★★★★☆(43) ⭐
• Exploratory Data Analysis from Johns Hopkins University ★★★★☆(38)
• Introduction to Big Data from University of California, San Diego ★★★☆☆(35)
• Regression Models from Johns Hopkins University ★★★☆☆(33)
• Statistical Inference from Johns Hopkins University ★★★☆☆(32)
• Introduction to Computational Thinking and Data Science from Massachusetts Institute of Technology ★★★★☆(30)
• Reproducible Research from Johns Hopkins University ★★★★☆(26)
• Hadoop Platform and Application Framework from University of California, San Diego ★★☆☆☆(25)
• Mining Massive Datasets from Stanford University ★★★★★(25)
• Statistics and R from Harvard University ★★★★☆(21)
• Pattern Discovery in Data Mining from University of Illinois at Urbana-Champaign ★★☆☆☆(21)
• A Crash Course in Data Science from Johns Hopkins University ★★★☆☆(20)
• Data Visualization from University of Illinois at Urbana-Champaign ★★★☆☆(20)
• Statistical Thinking for Data Science and Analytics from Columbia University ★★☆☆☆(19)
• Developing Data Products from Johns Hopkins University ★★★★☆(18)
• Building a Data Science Team from Johns Hopkins University ★★★★☆(12)
• Probability and Statistics in Data Science using Python from University of California, San Diego ★★☆☆☆(11)
• Data Analysis for Social Scientists from Massachusetts Institute of Technology ★★★☆☆(11)
• Text Mining and Analytics from University of Illinois at Urbana-Champaign ★★★★☆(10)
• Data Science in Real Life from Johns Hopkins University ★★★☆☆(10)
• Data Science: R Basics from Harvard University ★★★★★(8)
• Managing Data Analysis from Johns Hopkins University ★★☆☆☆(7)
• Applied Plotting, Charting & Data Representation in Python from University of Michigan ★★★☆☆(7)
• Cluster Analysis in Data Mining from University of Illinois at Urbana-Champaign ★★★☆☆(7)
• Foundations of Data Analysis - Part 1: Statistics Using R from The University of Texas at Austin ★★★★☆(6)
• Graph Analytics for Big Data from University of California, San Diego ★★★☆☆(6)
• People Analytics from University of Pennsylvania ★★★★☆(5)
• SP20: Computing for Data Analysis from Georgia Institute of Technology ★★★☆☆(5)
• The R Programming Environment from Johns Hopkins University ★★★☆☆(4)
• FA19: Deterministic Optimization from Georgia Institute of Technology ★★★★☆(4)
• Introduction to Analytics Modeling from Georgia Institute of Technology ★★★★☆(4)
• Data Manipulation at Scale: Systems and Algorithms from University of Washington ★★★☆☆(4)
• Data Science: Visualization from Harvard University ★★★★★(3)
• High-Dimensional Data Analysis from Harvard University ★★★★☆(3)
• Introduction to Systematic Review and Meta-Analysis from Johns Hopkins University ★★★★★(3)
• Big Data Modeling and Management Systems from University of California, San Diego ★★★☆☆(3)
• Big Data Integration and Processing from University of California, San Diego ★★★★☆(3)
• Data Science: Linear Regression from Harvard University ★★★☆☆(2)
• Data Science: Machine Learning from Harvard University ★★★★☆(2)
• Applied Social Network Analysis in Python from University of Michigan ★★★★★(2)
• Building R Packages from Johns Hopkins University ★★★☆☆(2)
• Foundations of Data Science: Computational Thinking with Python from University of California, Berkeley ★★★★★(2)
• Communicating Data Science Results from University of Washington ★☆☆☆☆(2)
• Causal Diagrams: Draw Your Assumptions Before Your Conclusions from Harvard University ★★★★★(2)
• Case study: DNA methylation data analysis from Harvard University ★★★★★(2)
• Foundations of Data Analysis - Part 2: Inferential Statistics from The University of Texas at Austin ★★★★☆(2)
• Framework for Data Collection and Analysis from University of Maryland, College Park ★★★★☆(2)
• 数据挖掘：理论与算法 | Data Mining: Theories and Algorithms for Tackling Big Data from Tsinghua University ★★★☆☆(2)
• Data Analytics Foundations for Accountancy I from University of Illinois at Urbana-Champaign ★☆☆☆☆(1)
• Successfully Evaluating Predictive Modelling from University of Edinburgh ★★☆☆☆(1)
• Silicon Photonics Design, Fabrication and Data Analysis from The University of British Columbia ★★★★★(1)
• Data Science: Inference and Modeling from Harvard University ★★★★☆(1)
• Data Science: Probability from Harvard University ★★★☆☆(1)
• Data Science: Productivity Tools from Harvard University ★★★★★(1)
• Data Science: Wrangling from Harvard University ★★★★★(1)
• Advanced Linear Models for Data Science 1: Least Squares from Johns Hopkins University ★★★★★(1)
• Advanced Linear Models for Data Science 2: Statistical Linear Models from Johns Hopkins University ★★★★★(1)
• Research Data Management and Sharing from The University of North Carolina at Chapel Hill ★★★☆☆(1)
• Big Data and Education from Columbia University ★★★☆☆(1)
• Big Data Analysis with Scala and Spark from École Polytechnique Fédérale de Lausanne ★★★☆☆(1)
• Basic Data Processing and Visualization from University of California, San Diego ★★★☆☆(1)
• Information Visualization: Applied Perception from New York University (NYU) ★★★★★(1)
• Information Visualization: Foundations from New York University (NYU) ★★★★★(1)
• Information Visualization: Programming with D3.js from New York University (NYU) ★★★★★(1)
• Information Visualization: Advanced Techniques from New York University (NYU) ★★★★★(1)
• Data Science: Capstone from Harvard University
• Capstone Exam for Statistics and Data Science from Massachusetts Institute of Technology
• Advanced R Programming from Johns Hopkins University
• Foundations of Data Science: Inferential Thinking by Resampling from University of California, Berkeley
• Data, Models and Decisions in Business Analytics from Columbia University
• Code Free Data Science from University of California, San Diego
• SP20: Data Analytics for Business from Georgia Institute of Technology
• Data Science in Stratified Healthcare and Precision Medicine from University of Edinburgh
• Predictive Analytics using Machine Learning from University of Edinburgh
• Statistical Predictive Modelling and Applications from University of Edinburgh
• 人群与网络 from Peking University
• 医学统计学与SPSS软件（基础篇） from Peking University
• Combining and Analyzing Complex Data from University of Maryland, College Park
• Dealing With Missing Data from University of Maryland, College Park
• 数据科学导论|Data Science: A New Way of Thinking from Tsinghua University
• [New] Data Science for Construction, Architecture and Engineering from National University of Singapore
• Statistical Computing with R - a gentle introduction from University College London
• Principles, Statistical and Computational Tools for Reproducible Data Science from Harvard University
• Data Analysis in Social Science-Assessing Your Knowledge from Massachusetts Institute of Technology
• Sampling People, Networks and Records from University of Michigan
• مجموعة أدوات عالم البيانات from Johns Hopkins University
• Meaningful Predictive Modeling from University of California, San Diego
• Introduction to Accounting Data Analytics and Visualization from University of Illinois at Urbana-Champaign
• Data Modeling and Regression Analysis in Business from University of Illinois at Urbana-Champaign
• Introduction to Predictive Analytics using Python from University of Edinburgh
• Delivering Research Data Management Services from University of Edinburgh
• Image Processing and Analysis for Life Scientists from École Polytechnique Fédérale de Lausanne
• Data Analysis Essentials from Imperial College London
• Big Data Analytics Using Spark from University of California, San Diego
• مقدمة عن البيانات الضخمة from University of California, San Diego
• Big Data Analytics in Healthcare from Georgia Institute of Technology
• Big Data Analytics in Healthcare from Georgia Institute of Technology
• 高级大数据系统|Advanced Big Data Systems from Tsinghua University
• [New] Big data and Language 1 from Korea Advanced Institute of Science and Technology
• [New] Big data and Language 2 from Korea Advanced Institute of Science and Technology
• Building Data Visualization Tools from Johns Hopkins University
• Data Analysis and Visualization from Georgia Institute of Technology
• 3D Data Visualization for Science Communication from University of Illinois at Urbana-Champaign
• [New] 数据可视化|Data Visualization from Tsinghua University

Programming Languages — 60 Courses

• Programming for Everybody (Getting Started with Python) from University of Michigan ★★★★★(9662) ⭐
• Python Data Structures from University of Michigan ★★★★★(4369)
• Using Python to Access Web Data from University of Michigan ★★★★★(1903)
• Learn to Program: The Fundamentals from University of Toronto ★★★★★(105) ⭐
• Python and Statistics for Financial Analysis from The Hong Kong University of Science and Technology ★★★★☆(71) ⭐
• Computing in Python I: Fundamentals and Procedural Programming from Georgia Institute of Technology ★★★★★(69) ⭐
• Functional Program Design in Scala from École Polytechnique Fédérale de Lausanne ★★★★★(40)
• Computing in Python IV: Objects & Algorithms from Georgia Institute of Technology ★★★★★(36)
• Computing in Python II: Control Structures from Georgia Institute of Technology ★★★★★(27)
• Programming Languages, Part A from University of Washington ★★★★★(22)
• Computing in Python III: Data Structures from Georgia Institute of Technology ★★★★★(21)
• Object Oriented Programming in Java from University of California, San Diego ★★★★★(15)
• Introduction to Programming for the Visual Arts with p5.js from University of California, Los Angeles ★★★★★(10)
• Using Python for Research from Harvard University ★★★☆☆(9)
• Learn to Program: Crafting Quality Code from University of Toronto ★★★★☆(9)
• Code Yourself! An Introduction to Programming from University of Edinburgh ★★★★★(8)
• Introduction To Swift Programming from University of Toronto ★☆☆☆☆(7)
• Parallel programming from École Polytechnique Fédérale de Lausanne ★★★★☆(6)
• MATLAB and Octave for Beginners from École Polytechnique Fédérale de Lausanne ★★★★☆(6)
• Introduction to Java Programming – Part 1 from The Hong Kong University of Science and Technology ★★★☆☆(6)
• Programming for the Web with JavaScript from University of Pennsylvania ★★★★★(4)
• Web Coding Fundamentals: HTML, CSS and Javascript from National University of Singapore ★★★★★(3)
• Introduction à la programmation orientée objet (en C++) from École Polytechnique Fédérale de Lausanne ★★★☆☆(3)
• Initiation à la programmation (en C++) from École Polytechnique Fédérale de Lausanne ★★★★★(3)
• Language, Proof and Logic from Stanford University ★★★★★(2)
• ¡A Programar! Una introducción a la programación from University of Edinburgh ★★★★★(1)
• 计算导论与C语言基础 from Peking University ★★★★☆(1)
• Introduction à la programmation orientée objet (en Java) from École Polytechnique Fédérale de Lausanne ★★★★★(1)
• Creative Coding from New York University (NYU) ★★★★☆(1)
• Lernen objekt-orientierter Programmierung from Technische Universität München (Technical University of Munich) ★★★★★(1)
• Initiation à la programmation (en Java) from École Polytechnique Fédérale de Lausanne ★★★★★(1)
• Einführung in MATLAB from Technische Universität München (Technical University of Munich)
• Quantitative Methods for Biology from Harvard University
• Programación para todos (empezando con Python) from University of Michigan
• Introduction to Neurohacking In R from Johns Hopkins University
• Minecraft, Coding and Teaching from University of California, San Diego
• برمج بنفسك! مقدمة حول البرمجة from University of Edinburgh
• 程序设计基础 from Peking University
• 面向对象技术高级课程（The Advanced Object-Oriented Technology） from Peking University
• MATLAB et Octave pour débutants from École Polytechnique Fédérale de Lausanne
• Python Data Structures from University of Michigan
• Programming for Everybody (Getting Started with Python) from University of Michigan
• Python Basics from University of Michigan
• Understanding and Visualizing Data with Python from University of Michigan
• Python Functions, Files, and Dictionaries from University of Michigan
• البرمجة للجميع - بدء استخدام بايثون from University of Michigan
• Data Collection and Processing with Python from University of Michigan
• Python Classes and Inheritance from University of Michigan
• Inferential Statistical Analysis with Python from University of Michigan
• Programming for Everybody (Getting Started with Python) from University of Michigan
• Fitting Statistical Models to Data with Python from University of Michigan
• Programming Reactive Systems from École Polytechnique Fédérale de Lausanne
• Real-Time Audio Signal Processing in Faust from Stanford University
• Java 程序设计 Java Programming from Peking University
• Introduction to Java Programming – Part 2 from The Hong Kong University of Science and Technology
• Projet de programmation (en Java) from École Polytechnique Fédérale de Lausanne
• C++程序设计 from Peking University
• C++ 程序设计 from Peking University
• C程序设计进阶 from Peking University
• C#程序设计 from Peking University

Software Development — 57 Courses

• Ruby on Rails: An Introduction from Johns Hopkins University ★★★☆☆(56)
• Introduction to HTML5 from University of Michigan ★★★★☆(42) ⭐
• Programming Mobile Applications for Android Handheld Systems: Part 1 from University of Maryland, College Park ★★★★☆(38)
• Cloud Computing Concepts, Part 1 from University of Illinois at Urbana-Champaign ★★★☆☆(21)
• Agile Development Using Ruby on Rails - The Basics from University of California, Berkeley ★★★★☆(19)
• Programming Mobile Applications for Android Handheld Systems: Part 2 from University of Maryland, College Park ★★★★☆(15)
• HTML, CSS, and Javascript for Web Developers from Johns Hopkins University ★★★★★(14)
• Introduction to CSS3 from University of Michigan ★★★★★(13)
• Interactivity with JavaScript from University of Michigan ★★★★☆(11)
• Advanced Styling with Responsive Design from University of Michigan ★★★★☆(8)
• Software Development Process from Georgia Institute of Technology ★★★★☆(5)
• Cloud Networking from University of Illinois at Urbana-Champaign ★★★★☆(5)
• CS50's Web Programming with Python and JavaScript from Harvard University ★★★★★(4)
• Single Page Web Applications with AngularJS from Johns Hopkins University ★★★★★(4)
• Cloud Computing Concepts: Part 2 from University of Illinois at Urbana-Champaign ★★★★★(4)
• Agile Development Using Ruby on Rails - Advanced from University of California, Berkeley ★★★★★(4)
• Agile Software Development from ETH Zurich ★★★★☆(3)
• Mastering the Software Engineering Interview from University of California, San Diego ★★★★☆(3)
• Software Engineering Essentials from Technische Universität München (Technical University of Munich) ★★★★☆(2)
• Mobile Application Experiences Part 1: From a Domain to an App Idea from Massachusetts Institute of Technology ★★★★★(2)
• The Computing Technology Inside Your Smartphone from Cornell University ★★★★★(2)
• Introduction to Mobile Application Development using Android from The Hong Kong University of Science and Technology ★★★★☆(2)
• iOS App Development Basics from University of Toronto ★★★★☆(2)
• App Design and Development for iOS from University of Toronto ★★★☆☆(2)
• Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud from University of Illinois at Urbana-Champaign ★★★☆☆(2)
• CS50's Mobile App Development with React Native from Harvard University ★★★★☆(1)
• Software Development Fundamentals from University of Pennsylvania ★★★☆☆(1)
• Building Web Applications in PHP from University of Michigan ★★★★★(1)
• Building Database Applications in PHP from University of Michigan ★★★★★(1)
• Server-side Development with NodeJS, Express and MongoDB from The Hong Kong University of Science and Technology ★★★★★(1)
• Make Your Own App from Technische Universität München (Technical University of Munich) ★★★★★(1)
• CS50's Introduction to Game Development from Harvard University ★★★★★(1)
• Software Analysis & Testing from Georgia Institute of Technology
• Introduction to Internationalization and Localization from University of Washington
• Java程序设计 from Peking University
• Mobile Application Experiences Part 3: Building Mobile Apps from Massachusetts Institute of Technology
• Mobile Application Experiences Part 4: Understanding Use from Massachusetts Institute of Technology
• Mobile Application Experiences Part 5: Reporting Research Findings from Massachusetts Institute of Technology
• Mobile Application Experiences from Massachusetts Institute of Technology
• Developing Android Apps with App Inventor from The Hong Kong University of Science and Technology
• Multiplatform Mobile App Development with React Native from The Hong Kong University of Science and Technology
• Multiplatform Mobile App Development with NativeScript from The Hong Kong University of Science and Technology
• Multiplatform Mobile App Development with Web Technologies: Ionic and Cordova from The Hong Kong University of Science and Technology
• 3D Graphics in Android: Sensors and VR from Imperial College London
• Android Graphics with OpenGL ES from Imperial College London
• Introduction to Android graphics from Imperial College London
• Advanced App Development in Android Capstone from Imperial College London
• Build Your Own iOS App from University of Toronto
• JavaScript, jQuery, and JSON from University of Michigan
• Front-End Web UI Frameworks and Tools: Bootstrap 4 from The Hong Kong University of Science and Technology
• Web App Development with the Power of Node.js from Technische Universität München (Technical University of Munich)
• Introduction to Web Cartography: Part 1 from ETH Zurich
• Front-End JavaScript Frameworks: Angular from The Hong Kong University of Science and Technology
• Front-End Web Development with React from The Hong Kong University of Science and Technology
• Semantic Modelling from National University of Singapore
• How Virtual Reality Works from University of California, San Diego
• Creating Virtual Reality (VR) Apps from University of California, San Diego

Quantum Computing — 7 Courses

• Quantum Information Science I, Part 1 from Massachusetts Institute of Technology ★★☆☆☆(2)
• Quantum Machine Learning from University of Toronto ★★★★★(1)
• Quantum Information Science I, Part 2 from Massachusetts Institute of Technology
• Quantum Information Science II, Part 3 - Advanced quantum algorithms and information theory from Massachusetts Institute of Technology
• Quantum Information Science II, Part 1 - Quantum states, noise and error correction from Massachusetts Institute of Technology
• Quantum Information Science I, Part 3 from Massachusetts Institute of Technology
• Quantum Information Science II, Part 2 - Efficient Quantum Computing - fault tolerance and complexity from Massachusetts Institute of Technology