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

(15 Lectures Available)


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 2. Optimization Problems (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
3 3. Graph-theoretic Models (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
4 4. Stochastic Thinking (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
5 5. Random Walks (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
6 6. Monte Carlo Simulation (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
7 7. Confidence Intervals (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
8 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
9 9. Understanding Experimental Data (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
10 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
11 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
12 12. Clustering (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
13 13. Classification (M-I-T) Introduction to Computational Thinking and Data Science, Fall 2016 (M-I-T) MIT John Guttag Applied Sciences
14 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
15 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

of 1 15 Lectures Available.