400

This course allows students to integrate what they have learned throughout the curriculum in an applied, real world setting. Students work in teams on a major project, applying software engineering principles along the way. The course also emphasizes professional presentations and technical reports at various points in the project. This is the first half of the senior capstone experience, where teams will begin their work on a major project.

This course allows students to integrate what they have learned throughout the curriculum in an applied, real world setting. Students work in teams on a major project, applying software engineering principles along the way. The course also emphasizes professional presentations and technical reports at various points in the project. This is the second half of the senior capstone experience, where teams will finish their work on a major project and present their results.

An overview of AI, including history, impact, implications, and the potential of artificial intelligence. Machine learning: perceptrons, multi-layer networks, and deep learning. Classical AI: game playing and search, propositional logic, first order logic, inference. Knowledge representation.

Techniques for specifying the syntax and semantics of programming languages, including language concepts, execution environments, comparative analysis of programming languages. Principles of compiler design, including lexical analysis, syntax analysis, error detection and recovery.

Independent project developed under the guidance of a Computer Science faculty member. Students can apply by consulting with and submitting a project proposal to a Computer Science faculty member for 1-4 credits.

A special topics course that allows faculty members to explore topics in computer science. May be repeated for additional credit, with a maximum of 8 credits total.