This course introduces the design and analysis of fundamental algorithms. It focuses on the basic skills needed to design efficient, correct algorithms and mathematically prove these properties. General problem-solving techniques covered: divide-and-conquer, dynamic programming, greediness, and probabilistic algorithms. Topics include: sorting, searching, graph algorithms, optimization, network flows, asymptotic analysis, compression, and NP-completeness.

Units: 1

Max Enrollment: 24

Prerequisites: One of the following (CS 230, CS 230P, or CS 230X) and MATH 225, or permission of the instructor.

Distribution Requirements: MM - Mathematical Modeling and Problem Solving

Typical Periods Offered: Spring; Fall

Semesters Offered this Academic Year: Fall; Spring

Notes: