| 1 | Lecture 1: Introduction and Optimization Problems (PDF) |
Additional Files for Lecture 1 (ZIP) (This ZIP file contains: 1 .txt file and 1 .py file) |
| 2 | Lecture 2: Optimization Problems (PDF - 6.9MB) |
Additional Files for Lecture 2 (ZIP) (This ZIP file contains: 1 .txt file and 1 .py file) |
| 3 | Lecture 3: Graph-theoretic Models (PDF) | Code File for Lecture 3 (PY) |
| 4 | Lecture 4: Stochastic Thinking (PDF) | Code File for Lecture 4 (PY) |
| 5 | Lecture 5: Random Walks (PDF) | Code File for Lecture 5 (PY) |
| 6 | Lecture 6: Monte Carlo Simulation (PDF - 1.2MB) | Code File for Lecture 6 (PY) |
| 7 | Lecture 7: Confidence Intervals (PDF) | Code File for Lecture 7 (PY) |
| 8 | Lecture 8: Sampling and Standard Error (PDF - 1.3MB) |
Additional Files for Lecture 8 (ZIP - 1.6MB) (This ZIP file contains: 1 .csv file and 1 .py file) |
| 9 | Lecture 9: Understanding Experimental Data (PDF) |
Additional Files for Lecture 9 (ZIP) (This ZIP file contains: 4 .txt files and 1 .py file) |
| 10 | Lecture 10: Understanding Experimental Data (cont.) (PDF - 1.3MB) |
Additional Files for Lecture 10 (ZIP - 1.7MB) (This ZIP file contains: 1 .csv file, 7 .txt files, and 2 .py files) |
| 11 | Lecture 11: Introduction to Machine Learning (PDF - 1.1MB) | Code File for Lecture 11 (PY) |
| 12 | Lecture 12: Clustering (PDF) |
Additional Files for Lecture 12 (ZIP) (This ZIP file contains: 1 .txt file and 2 .py files) |
| 13 | Lecture 13: Classification (PDF) |
Additional Files for Lecture 13 (ZIP) (This ZIP file contains: 1 .txt file and 1 .py file) |
| 14 | Lecture 14: Classification and Statistical Sins (PDF) |
Additional Files for Lecture 14 (ZIP) (This ZIP file contains: 1 .txt file and 1 .py file) |
| 15 | Lecture 15: Statistical Sins and Wrap Up (PDF - 1.1MB) | Code File for Lecture 15 (PY) |
