Introduction to Probability for Computer Scientists

Overview

Examine the application of probability in the computer science field and how it is used in the analysis of algorithms. Learn how probability theory has become a powerful computing tool and what current trends are causing the need for probabilistic analysis. Acquire an important understanding about randomness and its influence on the computing decisions made every day.

Topics Include

• Counting and combinatorics
• Conditional probability
• Distributions
• Point estimation
• Limit theorems

Instructors

• Mehran Sahami Associate Professor, Computer Science

Units

3.0 - 5.0

Students enrolling under the non degree option are required to take the course for 5.0 units.

Grading

• Problem Sets- 45%
• Midterm- 20%
• Final- 35%

Prerequisites

Mathematical Foundations of Computing (Stanford Course: CS103), and Programming Abstractions (Stanford Course:CS106B) or Accelerated Programming Abstractions (Stanford Course:CS106X), and Linear Algebra and Differential Calculus (Stanford Course: MATH51) or equivalent.