Lecture Slides and Files

SES # LECTURE SLIDES CODE AND ADDITIONAL FILES
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)

Course Info

Learning Resource Types

theaters Lecture Videos
assignment Problem Sets
notes Lecture Notes
assignment Programming Assignments