Como todos los meses, os traemos un lista de cursos online, en este caso de programación, que destacamos por su positiva valoración y relevancia. La lista de este mes de mayo es muy grande, con muchos cursos ya cursados y valorados por los usuarios:

• 53 cursos de nivel básico
• 129 cursos de nivel intermedio
• 46 cursos de nivel avanzado

Nivel básico

1. Programming for Everybody (Getting Started with Python) – University of Michigan ★★★★★(2626)
2. Introduction to Computer Science and Programming Using Python – Massachusetts Institute of Technology ★★★★★(115)
3. Learn to Program: The Fundamentals – University of Toronto★★★★★(100)
4. Intro to Computer Science – University of Virginia ★★★★☆(68)
5. CS50’s Introduction to Computer Science – Harvard University★★★★★(67)
6. Ruby on Rails: An Introduction – Johns Hopkins University★★★☆☆(55)
7. Introduction to Linux – Linux Foundation ★★★★☆(37)
8. Internet History, Technology, and Security – University of Michigan★★★★★(36)
9. Introduction to VBA/Excel Programming – Cal Poly Pomona★★★★☆(26)
10. [New] Introducción a la programación en Java: estructuras de datos y algoritmos – Universidad Carlos iii de Madrid
11. Build a Modern Computer – First Principles: – Nand to Tetris (Project-Centered Course) – Hebrew University of Jerusalem★★★★★(23)
12. Introduction to Cyber Security – The Open University ★★★★☆(19)
13. Introducción a la programación orientada a objetos en Java – Universidad de los Andes ★★★★★(17)
14. CS101: Computer Science 101 – Stanford University ★★★★☆(15)
15. Web Security Fundamentals – KU Leuven University ★★★★☆(13)
16. Networking: Introduction to Computer Networking – Stanford University ★★★★★(11)
17. Creative Programming for Digital Media & Mobile Apps – University of London International Programmes ★★★★☆(11)
18. HTML, CSS, and Javascript for Web Developers – Johns Hopkins University ★★★★★(10)
19. Introduction to the Internet of Things and Embedded Systems – University of California, Irvine ★★★★☆(10)
20. HTML5 Coding Essentials and Best Practices – World Wide Web Consortium (W3C) ★★★★☆(9)
21. Introduction to Programming for the Visual Arts with p5.js – University of California, Los Angeles ★★★★★(7)
22. Python Programming: A Concise Introduction – Wesleyan University★★★☆☆(5)
23. Introduction to jQuery – Microsoft ★★★★☆(5)
24. HTML5 and CSS Fundamentals – World Wide Web Consortium (W3C)★★★★☆(5)
25. Introduction to Java Programming — Part 1 – The Hong Kong University of Science and Technology ★★★★☆(4)
26. Introduction to Java Programming: Starting to code in Java – Universidad Carlos iii de Madrid ★★★★☆(4)
27. Paradigms of Computer Programming — Fundamentals – Université catholique de Louvain ★★★★★(4)
28. Paradigms of Computer Programming — Abstraction and Concurrency– Université catholique de Louvain ★★★★☆(4)
29. Programming in Scratch – Harvey Mudd College ★★★★★(4)
30. How To Create a Website in a Weekend! (Project-Centered Course) – State University of New York ★★★★★(3)
31. Programming for the Web with JavaScript – University of Pennsylvania★★★★★(2)
32. The Beauty and Joy of Computing — AP® CS Principles Part 1 – University of California, Berkeley ★★★★★(2)
33. Introduction to Computing using Python – Georgia Institute of Technology ★★★★★(2)
34. How to Code: Simple Data – The University of British Columbia★★★★★(2)
35. Object-Oriented Programming – Indian Institute of Technology Bombay★★★★☆(2)
36. Think. Create. Code – University of Adelaide ★★★★★(2)
37. The Computing Technology Inside Your Smartphone – Cornell University ★★★★★(2)
38. Android Basics: Make Your First App – Google ★★★★☆(2)
39. Learn to Program Using Python – University of Texas Arlington★★★★★(2)
40. Introduction to HTML and JavaScript – Microsoft ★★★★★(2)
41. CS For All: Introduction to Computer Science and Python Programming– Harvey Mudd College ★★★★★(2)
42. CS50’s AP® Computer Science Principles – Harvard University★★★★★(1)
43. CS50’s Computer Science for Business Professionals – Harvard University ★★★★★(1)
44. Introduction to Structured Query Language (SQL) – University of Michigan ★★★★★(1)
45. Web Development and Design using WordPress – California Institute of the Arts ★★★★☆(1)
46. Web Coding Fundamentals for Artists – National University of Singapore ★★★★☆(1)
47. Learn to Program in Java – Microsoft ★★★★★(1)
48. Introduction to Node.js – Microsoft ★★★★★(1)
49. Computing: Art, Magic, Science – ETH Zurich ★★★★☆(1)
50. Software Engineering Essentials – Technische Universität München (Technical University of Munich) ★★★★★(1)
51. Lernen objekt-orientierter Programmierung – Technische Universität München (Technical University of Munich) ★★★★★(1)
52. MyCS: Computer Science for Beginners – Harvey Mudd College★★★☆☆(1)
53. CODAPPS: Coding mobile apps for entrepreneurs – EMLYON Business School ★★★★★(1)

Nivel intermedio

1. Python Data Structures– University of Michigan ★★★★★(1589)
2. Using Python to Access Web Data– University of Michigan★★★★★(832)
3. Using Databases with Python– University of Michigan ★★★★★(721)
4. Functional Programming Principles in Scala– École Polytechnique Fédérale de Lausanne ★★★★★(63)
5. Algorithms, Part I– Princeton University ★★★★★(58)
6. Machine Learning for Musicians and Artists– Goldsmiths, University of London ★★★★★(58)
7. Cryptography I– Stanford University ★★★★★(49)
8. Functional Program Design in Scala– École Polytechnique Fédérale de Lausanne ★★★★★(38)
9. Programming Mobile Applications for Android Handheld Systems: Part 1– University of Maryland, College Park★★★★☆(38)
10. 1x: Artificial Intelligence– University of California, Berkeley★★★★★(30)
11. Responsive Website Basics: Code with HTML, CSS, and JavaScript – University of London International Programmes★★★★☆(24)
12. Programming Languages, Part A– University of Washington★★★★★(22)
13. Algorithms, Part II– Princeton University ★★★★★(21)
14. Cloud Computing Concepts, Part 1– University of Illinois at Urbana-Champaign ★★★☆☆(21)
15. Automata Theory– Stanford University ★★★★☆(18)
16. Intro to Machine Learning– Stanford University ★★★★☆(18)
17. Agile Development Using Ruby on Rails — The Basics– University of California, Berkeley ★★★★★(18)
18. Android Development for Beginners– Google ★★★★☆(17)
19. C++ For C Programmers, Part A– University of California, Santa Cruz★★★☆☆(16)
20. The Nature of Code– Processing Foundation ★★★★★(16)
21. Programming Mobile Applications for Android Handheld Systems: Part 2– University of Maryland, College Park★★★★☆(15)
22. Design of Computer Programs– Stanford University ★★★★☆(13)
23. Text Retrieval and Search Engines– University of Illinois at Urbana-Champaign ★★★☆☆(13)
24. The Arduino Platform and C Programming– University of California, Irvine ★★★☆☆(12)
25. Discrete Optimization– University of Melbourne ★★★★☆(12)
26. Introduction to Functional Programming– Delft University of Technology ★★★★☆(11)
27. Developing Android Apps– Google ★★★☆☆(11)
28. Object-Oriented JavaScript– Hack Reactor ★★★★★(11)
29. Programming Languages– University of Virginia ★★★☆☆(10)
30. Introduction to Software Product Management– University of Alberta★★★★☆(9)
31. Data Wrangling with MongoDB– MongoDB University ★★★☆☆(9)
32. Cryptography– University of Maryland, College Park ★★★★☆(8)
33. Learning – Data (Introductory Machine Learning course)– California Institute of Technology ★★★★★(8)
34. Software Processes and Agile Practices– University of Alberta★★★★☆(8)
35. Responsive Web Design Fundamentals– Google ★★★★★(8)
36. Julia Scientific Programming– University of Cape Town ★★★★★(8)
37. Software Testing– University of Utah ★★★★☆(7)
38. Ruby on Rails Web Services and Integration with MongoDB– Johns Hopkins University ★★★★★(6)
39. Interfacing with the Arduino– University of California, Irvine★★★★☆(6)
40. Computer Architecture– Princeton University ★★★★☆(6)
41. Web Application Development with JavaScript and MongoDB– University of London International Programmes ★★★★☆(6)
42. How to Code: Systematic Program Design — Part 1– The University of British Columbia ★★★★☆(6)
43. Client Needs and Software Requirements – University of Alberta★★★★★(6)
44. Cybersecurity Fundamentals– Rochester Institute of Technology★★★★★(6)
45. Intro to DevOps– Nutanix ★★★☆☆(6)
46. Software Construction in Java– Massachusetts Institute of Technology★★★★★(5)
47. Computer Graphics– University of California, Berkeley ★★★★☆(5)
48. The Raspberry Pi Platform and Python Programming for the Raspberry Pi– University of California, Irvine★★★☆☆(5)
49. Software Development Process– Georgia Institute of Technology★★★★☆(5)
50. Computer Networking– Georgia Institute of Technology ★★★★☆(5)
51. HTML5 Game Development– Google ★★★☆☆(5)
52. Introduction to C++– Microsoft ★★★★☆(5)
53. Software Debugging– Saarland University ★★★★★(5)
54. Using Python for Research– Harvard University ★★★☆☆(4)
55. Agile Development Using Ruby on Rails — Advanced– University of California, Berkeley ★★★★★(4)
56. Rails with Active Record and Action Pack– Johns Hopkins University★★★★☆(4)
57. Single Page Web Applications with AngularJS– Johns Hopkins University ★★★★★(4)
58. Analysis of Algorithms– Princeton University ★★★★★(4)
59. Java Programming: Principles of Software Design– Duke University★★★★★(4)
60. Cloud Networking– University of Illinois at Urbana-Champaign★★★★☆(4)
61. Internet of Things: Setting Up Your DragonBoard™ Development Platform– University of California, San Diego ★★★☆☆(4)
62. Internet of Things & Augmented Reality Emerging Technologies– Yonsei University ★★★☆☆(4)
63. Website Performance Optimization– Google ★★★★☆(4)
64. UX Design for Mobile Developers– Google ★★★★★(4)
65. Querying Data with Transact-SQL– Microsoft ★★★★☆(4)
66. Foundations of Objective-C App Development– University of California, Irvine ★★★☆☆(3)
67. Networks Illustrated: Principles without Calculus– Princeton University★★★★☆(3)
68. VLSI CAD Part I: Logic– University of Illinois at Urbana-Champaign★★★★★(3)
69. Game Development for Modern Platforms– Michigan State University★★★★★(3)
70. MATLAB and Octave for Beginners– École Polytechnique Fédérale de Lausanne ★★★☆☆(3)
71. Wireless Communication Emerging Technologies– Yonsei University★★★★☆(3)
72. Android Basics: User Input– Google ★★★★☆(3)
73. VR Software Development– Google ★★★☆☆(3)
74. JavaScript Promises– Google ★★★★★(3)
75. Android Basics: Multiscreen Apps– Google ★★★★☆(3)
76. DevOps for Developers: How to Get Started– Microsoft ★★★★☆(3)
77. Agile Software Development– ETH Zurich ★★★★☆(3)
78. Autonomous Mobile Robots– ETH Zurich ★★★☆☆(3)
79. LPL: Language, Proof and Logic– Stanford University ★★★★★(2)
80. Compilers– Stanford University ★★★★☆(2)
81. Mobile Application Experiences Part 1: – a Domain to an App Idea– Massachusetts Institute of Technology★★★★★(2)
82. Interfacing with the Raspberry Pi– University of California, Irvine★★★☆☆(2)
83. Machine Learning: Unsupervised Learning– Brown University★★★★★(2)
84. Programming Languages, Part B– University of Washington★★★★★(2)
85. App Design and Development for iOS– University of Toronto★★★☆☆(2)
86. Introduction to Mobile Application Development using Android– The Hong Kong University of Science and Technology ★★★★☆(2)
87. Internet Emerging Technologies– Yonsei University ★★★☆☆(2)
88. Client-Server Communication– Google ★★★★★(2)
89. Android Basics: Networking– Google ★★★★☆(2)
90. Browser Rendering Optimization– Google ★★★★☆(2)
91. Developing International Software, Part 1– Microsoft ★★★★☆(2)
92. Analyzing and Visualizing Data with Power BI– Microsoft ★★★★★(2)
93. Build Your First Android App (Project-Centered Course)– École Centrale Paris ★★★☆☆(2)
94. Approximation Algorithms Part I– École normale supérieure★★★★★(2)
95. Computation Structures 2: Computer Architecture– Massachusetts Institute of Technology ★★★★☆(1)
96. Software Development Fundamentals– University of Pennsylvania★★★☆☆(1)
97. Best Practices for iOS User Interface Design– University of California, Irvine ★★★★★(1)
98. Software Architecture & Design– Georgia Institute of Technology★★★★★(1)
99. Database Systems Concepts & Design– Georgia Institute of Technology★★★★☆(1)
100. Animation and CGI Motion– Columbia University ★★★☆☆(1)
101. Programming Languages, Part C– University of Washington★★★★★(1)

102. 3D Models for Virtual Reality– University of London International Programmes ★★★★★(1)
103. How to Code: Complex Data– The University of British Columbia★★★★★(1)
104. Getting Started: Agile Meets Design Thinking– University of Virginia★★★★★(1)
105. Agile Software Development– University of Minnesota ★★★★☆(1)
106. Web Application Development: Basic Concepts– University of New Mexico ★★★★☆(1)
107. Algorithms– Indian Institute of Technology Bombay ★★★★★(1)
108. Android: Introducción a la Programación– Universitat Politècnica de València ★★★★☆(1)
109. Agile Planning for Software Products– University of Alberta★★★☆☆(1)
110. Software Architecture for the Internet of Things– EIT Digital ★★★★☆(1)

111. Material Design for Android Developers– Google★★★★★(1)
112. Scalable Microservices with Kubernetes– Google★★★★☆(1)
113. Gradle for Android and Java– Google★★★★★(1)
114. Developing Scalable Apps in Python– Google★★★★☆(1)
115. Developing Scalable Apps in Java– Google★★★★☆(1)
116. Android Performance– Google★★★★★(1)
117. Android Basics: Button Clicks– Google★★★☆☆(1)
118. Asynchronous Programming with Javascript– Microsoft★★★★★(1)

119. Intermediate C++– Microsoft★★★★☆(1)
120. Principles of Machine Learning– Microsoft ★★★★★(1)
121. AngularJS: Advanced Framework Techniques– Microsoft★★★★☆(1)
122. Build a Modern Computer – First Principles: Nand to Tetris Part II (project-centered course)– Hebrew University of Jerusalem★★★★★(1)
123. 用Python玩转数据 Data Processing Using Python– Nanjing University★★★★★(1)
124. Introduction to Cloud Infrastructure Technologies– Linux Foundation★★★★☆(1)
125. 2D Game Development with libGDX– Amazon★★★★★(1)
126. Introduction to Real-Time Systems– IEEE★★★★☆(1)
127. How to Win Coding Competitions: Secrets of Champions– ITMO University★★★☆☆(1)

128. HTML5 Apps and Games– World Wide Web Consortium (W3C)★★★☆☆(1)
129. Technical Interview– Pramp★★★★★(1)

Nivel avanzado

1. Deep Learning– Google ★★☆☆☆(44)
2. [New] Practical Reinforcement Learning– Higher School of Economics
3. [New] Deep Learning in Computer Vision– Higher School of Economics
4. [New] Addressing Large Hadron Collider Challenges by Machine Learning– Higher School of Economics
5. [New] Fundamentals of Accelerated Computing with CUDA C/C++– Nvidia
6. [New] Fundamentals of Deep Learning for Computer Vision– Nvidia
7. Introduction to Artificial Intelligence– Stanford University★★★★☆(24)
8. Neural Networks for Machine Learning– University of Toronto★★★★☆(22)
9. Probabilistic Graphical Models 1: Representation– Stanford University★★★★☆(17)
10. Machine Learning for Data Science and Analytics– Columbia University★★★☆☆(15)
11. Bitcoin and Cryptocurrency Technologies– Princeton University★★★★★(15)
12. Machine Learning for Trading– Georgia Institute of Technology★★★☆☆(13)
13. Neural Networks and Deep Learning– ai ★★★★★(12)
14. Hardware Security– University of Maryland, College Park ★★★☆☆(11)
15. Artificial Intelligence (AI)– Columbia University ★★★★☆(9)
16. Computational Neuroscience– University of Washington ★★★★☆(8)
17. Reinforcement Learning– Brown University ★★★☆☆(7)
18. Introduction to Computer Vision– Georgia Institute of Technology★★★★★(6)
19. Intro to Parallel Programming– Nvidia ★★★★☆(6)
20. Interactive 3D Graphics– Autodesk ★★★★☆(6)
21. Machine Learning– Georgia Institute of Technology ★★★★★(5)
22. Applied Cryptography– University of Virginia ★★★★☆(5)
23. Practical Deep Learning For Coders, Part 1– ai ★★★★☆(5)
24. Advanced Operating Systems– Georgia Institute of Technology★★★★★(4)
25. Machine Learning– Columbia University ★★★★★(4)
26. Parallel programming– École Polytechnique Fédérale de Lausanne★★★★☆(4)
27. Introduction to Computer Architecture– Carnegie Mellon University★★★★★(4)
28. Probabilistic Graphical Models 2: Inference– Stanford University★★★★☆(3)
29. Applied Machine Learning in Python– University of Michigan★★★★☆(3)
30. Regression Modeling in Practice– Wesleyan University ★★★★☆(3)
31. Quantitative Formal Modeling and Worst-Case Performance Analysis– EIT Digital ★★★☆☆(3)
32. Structuring Machine Learning Projects– ai ★★★★★(2)
33. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization– ai ★★★★★(2)
34. Sequence Models– ai ★★★★★(2)
35. S191: Introduction to Deep Learning– Massachusetts Institute of Technology ★★★★☆(2)
36. Introduction to Operating Systems– Georgia Institute of Technology★★★★★(2)
37. S094: Deep Learning for Self-Driving Cars– Massachusetts Institute of Technology ★★★★☆(1)
38. Computational Photography– Georgia Institute of Technology★★★★☆(1)
39. Knowledge-Based AI: Cognitive Systems– Georgia Institute of Technology ★★★☆☆(1)
40. Computability, Complexity & Algorithms– Georgia Institute of Technology ★★★★★(1)
41. High Performance Computer Architecture– Georgia Institute of Technology ★★★★★(1)
42. Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud– University of Illinois at Urbana-Champaign ★★★★☆(1)
43. Learn TensorFlow and deep learning, without a Ph.D.– Google★★★★☆(1)
44. Sparse Representations in Signal and Image Processing: Fundamentals– Technion — Israel Institute of Technology★★★★★(1)
45. Blockchain for Business — An Introduction to Hyperledger Technologies– Linux Foundation★★★★☆(1)
46. Introduction to Cloud Foundry and Cloud Native Software Architecture– Linux Foundation★★★★★(1)

 

Fuente: Freecodecamp