SWE 485: Selected topics in software Software Engineering

This course serves as a broad introduction to artificial intelligence and machine learning. We will cover the fundamentals of supervised and unsupervised learning. We will focus on policy gradient methods in reinforcement learning. Students should be comfortable with calculus, probability, and linear algebra. This class covers a broad array of research topics and latest trends in systems designs to better support the next generation of AI applications, and applications of AI to optimize the architecture and the performance of systems.

Course objective:

1. Understand the role that humans play in crafting effective AI solutions 

2. Describe and analyze problems which occur across sciences, in allied professional fields. 

3. Discuss the core concepts related to advanced AI models, and algorithms to solve a certain problem 

4. Implement the structures and algorithms of AI techniques related to searching, reasoning, and machine learning.

5. Apply the basic principles, models, and algorithms of AI to recognize, model, and solve problems in the analysis and design of information systems.