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# 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.

### Tuition & Fees

For course tuition, reduced tuition (SCPD member companies and United States Armed forces), and fees, please click Tuition & Fees.

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