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Dec 17, 2025
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University General Course Catalog 2023-2024 ARCHIVED CATALOG: LINKS AND CONTENT ARE OUT OF DATE. CHECK WITH YOUR ADVISOR.
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CS 486 - Introduction to Convex Optimization (3 units)
This course will introduce basic concepts of convex optimization and algorithms for convex optimization (e.g., Newton’s method, gradient descent methods). We will concentrate on recognizing and solving convex optimization problems that arise in engineering applications. This course would benefit anyone who uses or will use scientific computing or optimization in engineering or related work (e.g., machine learning, robotics, computer graphics, algorithms & complexity, computational geometry).
Maximum units a student may earn: 3
Prerequisite(s): CS 202 with a “C” or better; MATH 330 .
Grading Basis: Graded
Units of Lecture: 3
Offered: Every Spring
Student Learning Outcomes
Upon completion of this course, students will be able to:
1. identify, formulate, analyze, and solve complex computing or engineering problems by applying principles of computing, engineering, science, and mathematics.
2. apply computer science theory and software development fundamentals to produce computing-based solutions.
Click here for course scheduling information. | Check course textbook information
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