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Apr 24, 2024
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CS 479 - Pattern Recognition (3 units)
Pattern recognition systems, statistical methods, discrimination functions, clustering analysis, unsupervised learning, feature extraction and feature processing.
Prerequisite(s): CS 202 with a “C” or better; STAT 352 .
Units of Lecture: 3
Offered: Every Spring - Even Years
Student Learning Outcomes:
Upon completion of this course:
1. Students will have an ability to apply knowledge of computing, mathematics, science, and engineering.
2. Students will have an ability to communicate effectively with a range of audiences.
3. Students will have a recognition of the need for, and an ability to engage in continuing professional development and life-long learning.
4. Students will have an ability to use current techniques, skills, and tools necessary for computing and engineering practice.
5. Students will have an ability to apply mathematical foundations, algorithmic principles, and computer science and engineering theory in the modeling and design of computer-based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices.
6. Students will have an ability to apply design and development principles in the construction of software systems or computer systems of varying complexity.
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