Introduction to Computational Thinking and Data Science

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)