The textbook is 
Guttag, John. Introduction to Computation and Programming Using Python: With Application to Understanding Data. 2nd ed. MIT Press, 2016. ISBN: 9780262529624. [Preview with Google Books] It is available both in hard copy and as an e-book.
| SES # | TOPICS | READINGS |
|---|---|---|
| 1 | Introduction and Optimization Problems | Chapter 12.1, Chapter 5.4 |
| 2 | Optimization Problems | Chapter 13 |
| 3 | Graph-theoretic Models | Chapter 12.2 |
| 4 | Stochastic Thinking | Chapter 14 |
| 5 | Random Walks | Chapter 11, Chapter 14 |
| 6 | Monte Carlo Simulation | Chapter 15.1–15.4, Chapter 16 |
| 7 | Confidence Intervals | Chapter 16.4, Chapter 17 |
| 8 | Sampling and Standard Error | Chapter 17 |
| 9 | Understanding Experimental Data | Chapter 18 |
| 10 | Understanding Experimental Data (cont.) | Chapter 18 |
| 11 | Introduction to Machine Learning | Chapter 22 |
| 12 | Clustering | Chapter 23 |
| 13 | Classification | Chapter 24 |
| 14 | Classification and Statistical Sins | Chapter 21 |
| 15 | Statistical Sins and Wrap Up | Chapter 21 |
