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ELEC 472 Artificial Intelligence Units: 3.50
Fundamental concepts and applications of intelligent and interactive system design and implementation. Topics include: problem formulation and experiment design, search techniques and complexity, decision making and reasoning, data acquisition, data pre-processing (de-noising, missing data, source separation, feature extraction, feature selection, dimensionality reduction), supervised learning, unsupervised learning, and swarm intelligence.
(Lec: 3, Lab: 0.5, Tut: 0)
(Lec: 3, Lab: 0.5, Tut: 0)
Requirements: Prerequisites: ELEC 278 or MREN 178, ELEC 326 or
permission of the instructor
Corequisites:
Exclusions:
Offering Term: W
CEAB Units:
Mathematics 0
Natural Sciences 0
Complementary Studies 0
Engineering Science 31
Engineering Design 11
Offering Faculty: Smith Engineering
Course Learning Outcomes:
- Discuss communication technologies.
- Learn different methods of informed and uninformed search for problem solving and decision making.
- Learn to use logic and inference for decision making.
- Learn basic definitions, development, and applications of data preprocessing techniques.
- Learn basic definitions, development, and applications supervised and unsupervised machine learning models.
- Learn basic definitions, development, and applications of ensemble learning techniques.
- Learn basic definitions, development, and applications of evolutionary models.