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Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)

S#	Lecture	Course	Institute	Instructor	Discipline
1	1. Introduction, Optimization Problems (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
2	10. Understanding Experimental Data (cont.) (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
3	11. Introduction to Machine Learning (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
4	12. Clustering (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
5	13. Classification (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
6	14. Classification and Statistical Sins (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
7	15. Statistical Sins and Wrap Up (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
8	2. Optimization Problems (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
9	3. Graph-theoretic Models (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
10	4. Stochastic Thinking (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
11	5. Random Walks (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
12	6. Monte Carlo Simulation (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
13	7. Confidence Intervals (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
14	8. Sampling and Standard Error (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences
15	9. Understanding Experimental Data (M-I-T)	Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T)	MIT	John Guttag	Applied Sciences