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Probability and Data Analysis
for Computer Science

10-751 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 5-6 (take-home)

Course Information