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EE445 - Fundamentals of Optimization and Machine Learning

Available Universities

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Course: EE445 (Fundamentals of Optimization and Machine Learning) in E E department at University of Washington.

Credit Hours: 4 • Academic Level: fourth-year undergraduate course

Course Requirements: Requires 6 prerequisite courses

Prerequisite Chain Depth: 4 levels of foundational courses required

Interdisciplinary Requirements: Prerequisites span 4 different departments

Course Type: Capstone or specialized course - synthesizes prior learning

Part of the E E curriculum at University of Washington, helping students progress through degree requirements.

Prerequisites for EE445

MATH224
MATH136
MATH208
AMATH352
EE242
CSE163

Academic Planning at University of Washington

Students planning EE445 at University of Washington should complete 6 prerequisites before enrollment.

Course Sequence: This course requires a 4-level prerequisite chain, requiring careful multi-semester planning for optimal progression.

This fourth-year course at University of Washington integrates into structured degree pathways for E E programs, supporting timely graduation and academic progression.