A survey of machine learning topics including heuristic programming, search techniques, knowledge representation, expert systems, fuzzy logic, neural networks, evolutionary algorithms and swarm intelligence.
Prerequisite: CPSC 374 or permission of instructor. (3 credits)
This course and its outcomes support the Computing Learning Outcomes of Problem Solving and Critical Thinking (PS&CT), Communication and Interpersonal Skills (C&IS), and Ethical and Professional Responsibilities (E&PR). These Computing Learning Outcomes are tied directly to the University Wide Outcomes of Critical Thinking, Quantitative Reasoning, and Acting Ethically.
| Learning Outcomes | Course Objectives |
|---|---|
| E & PR a. Determine the economic and organizational effects of information technology on global society | 1. Explain what machine learning and robotics mean and how machines can be made to process information intelligently and perform physical human tasks. |
| 2. Describe different machine learning methods such as neural networks, expert systems, genetic algorithms and other machine learning paradigms. | |
| PS & CT d. Implement computing solutions that consist of system and application software written in various programming languages | 3. Write computer programs and/or use shell programs that solve problems intelligently. |
| PS & CT c. Perform critical analyses of the impacts of decisions based on mathematics | 4. Write programs in machine learning methods. |