MS in Computer Science

Artificial Intelligence

In order to get a Master Degree from World University, you must successfully complete 10 courses.

You can select them one by one, one after another or you may want to take breaks between courses.

To register for a course you wish to take:

1. Find the course on the list below.

2. Click on the University name.

3. A list of courses provided by that university will appear.

4. Find the course you wish to register in that list.

5. Click on the name of the course.

6. Follow the instructions to register the course.

7. After registration to the course go to "Operations", and inform us by "submit courses" button.

8. When you complete the course and get your certificate from the university go to "Operations" and inform us by "submit certificates" button.

The Best of the Best 40 courses for MS in Computer Science - Artificial Intelligence

(Available worldwide by top universities)

  1. Machine Learning I, Supervised Learning - Brown University

  2. Machine Learning, Unsupervised Learning - Brown University

  3. Reinforcement Learning - Brown University

  4. Machine Learning - Brown University

  5. Learning from DATA - California Institute of Technology

  6. Artificial Intelligence - Columbia University

  7. Machine Learning - Columbia University

  8. Machine Learning for Data Science, Analytics - Columbia University

  9. Autonomous Mobile Robots - ETH Zurich

  10. Knowledge Based AI - Georgia Institute of Technology

  11. Introduction to Computer Vision - Georgia Institute of Technology

  12. Machine Learning for Trading - Georgia Institute of Technology

  13. Machine Learning - Georgia Institute of Technology

  14. Practical Machine Learning - Johns Hopkins University

  15. Probabilistic Graphical Models I, Representation - Stanford University

  16. Machine Learning - Stanford University

  17. Probabilistic Graphical Models 2, Inference - Stanford University

  18. Artificial Intelligence for Robotics - Stanford University

  19. Introduction to Artificial Intelligence - Stanford University

  20. Artificial Intelligence for Robotics, Robo Car - Stanford University

  21. Introduction to Machine Learning - Stanford University

  22. Introduction to Artificial Intelligence - Stanford University

  23. Natural Language Processing - Stanford University

  24. Probabilistic Graphical Models 3 - Stanford University

  25. Autonomous Navigation for Flying Robots - Technische Universität München

  26. Introduction to Recommender Systems - University of Minnesota

  27. Nearest Neighbor Collaborative Filtering - University of Minnesota

  28. Machine Learning with Big Data - University of California

  29. Practical Deep Learning for Coders, Part I - University of San Francisco

  30. Machine Learning, Clustering & Retrieval - University of Washington

  31. Machine Learning Foundations, A Case Study - University of Washington

  32. Machine Learning, Classification - University of Washington

  33. Practical Predictive Analytics, Models, Methods - University of Washington

  34. Machine Learning, Regressions - University of Washington

  35. Computational Neuroscience - University of Washington

  36. Machine Learning - University of Washington

  37. Machine Learning, Recommender Systems - University of Washington

  38. Machine Learning for Data Analysis - Wesleyan University

  39. Regression Modeling in Practice - Wesleyan University

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