MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
4.0
(2)
24 learners
What you'll learn
This course includes
- 12 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 14 lessons • 12 hours of video
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
14 lessons
• 11.3 hours
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016
14 lessons
• 11.3 hours
- 1. Introduction, Optimization Problems (MIT 6.0002 Intro to Computational Thinking and Data Science) 40:57
- 2. Optimization Problems 48:04
- 3. Graph-theoretic Models 50:11
- 4. Stochastic Thinking 49:50
- 5. Random Walks 49:21
- 7. Confidence Intervals 50:29
- 8. Sampling and Standard Error 46:45
- 9. Understanding Experimental Data 47:06
- 10. Understanding Experimental Data (cont.) 50:33
- 11. Introduction to Machine Learning 51:31
- 12. Clustering 50:40
- 13. Classification 49:54
- 14. Classification and Statistical Sins 49:25
- 15. Statistical Sins and Wrap Up 44:43
Take this course with you
Download the app to continue lessons from your phone anytime.
