The class starts by providing a fundamental grounding in combinatorics, and then quickly moves into the basics of probability theory. We will then cover many essential concepts in probability theory, including particular probability distributions, properties of probabilities, and mathematical tools for analyzing probabilities. Finally, the last third of the class will focus on data analysis and Machine Learning as a means for seeing direct applications of probability in this exciting and quickly growing subfield of computer science.

The schedule is subject to change by the management at any time.

Week | Monday | Wednesday | Friday |
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1 | |||

2 |
Chapter 3.1-3.3 Oct 2nd Conditional Probability, Bayes TheoremSlides Lecture Notes Medical Test Demo |
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3 | |||

4 | |||

5 |
Due: PSet #3 Read: Chapter 6.4-6.5 Oct 25th Tracking in 2D Continuous SpaceSlides Lecture Notes Section 4 |
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6 | |||

7 | |||

8 | |||

9 |
Nov 20th Thanksgiving |
Nov 22nd Thanksgiving |
Nov 24th Thanksgiving |

10 | |||

11 |
Due: PSet #6 Dec 8th Dead Day |