
10751 gives an introduction to probability and data analysis
from a computer science perspective, treating many of the fundamental
concepts and techniques that are most relevant to current research
areas. Topics include the rudiments of probability and random
variables, estimation, special distributions and sampling, Markov
processes, hypothesis testing, graphics and visualization, matrix
methods and optimzation techniques.
What's New?
 (11/12) Exam 2: November 21 (in class);
Final: December 56 (takehome)
Course Information
