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# Introduction to Probability for Computer Scientists

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Introduction to Probability for Computer Scientists

## Overview

## Topics Include

## Instructors

## Units

## Grading

## Prerequisites

### Tuition & Fees

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.

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

- Mehran Sahami
*Associate Professor*,*Computer Science*

3.0 - 5.0

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

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

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.

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

Date:

Monday, January 4, 2016 to Friday, March 18, 2016

Course topic: