COMPSCI 240 (Reasoning Under Uncertainty) - 2020 Fall

Instructors

Peter Haas and Jie Xiong

Class

MoWe 2:30PM - 3:45PM

Course Description

Development of mathematical reasoning skills for problems that involve uncertainty. Each concept will be illustrated by real-world examples and demonstrated through in-class and homework exercises. Counting and probability -- basic counting problems, probability definitions, mean, variance, binomial distribution, discrete random variables, continuous random variables, Markov and Chebyshev bounds, Laws of large number, and central limit theorem. Probabilistic reasoning -- conditional probability and odds, Bayes' Law, Markov Chains, Bayesian Network, Markov Decision Processes.

Prerequisites

COMPSCI 187 and MATH 132 with a grade of 'C' or better.

More Information

  1. Moodle Moodle is going to be the primary communication platform for this class.

  2. Textbook: Introduction to Probability, 2nd Edition by Dimitri P. Bertsekas and John N. Tsitsiklis.

  3. Zoom link: Zoom links to all office hours are available on Moodle.

Grading Plan

  1. Weekly Quiz in Moodle (10 of them) 10%

  2. Homeworks (total 4) 20%

  3. Midterm 1 20%

  4. Midterm 2 20%

  5. Final 30%

Schedule