Program Learning Outcomes

The Artificial Intelligence emphasis is designed to give students a rigorous introduction to AI and its major sub-fields.
It emphasizes core AI techniques and methods while introducing more advanced, state-of-the-art practices. Machine learning, natural language processing, and computer vision are the main sub-fields stressed.

1. Demonstrate a working knowledge of Artificial Intelligence (AI) and its major subfields: computer vision, natural language processing, and machine learning.
2. Demonstrate a working knowledge of major AI tools, techniques, approaches, and subfields.
3. Gain a basic ability to develop AI software applications.
4. Exhibit an understanding of the major theological and ethical issues surrounding AI.

Computer Science Core Courses

Total units required for core courses: 59

• CS121P Introduction to Computer Programming
• CS122J JavaScript Essentials
• CS132S Data Structures & Algorithms
• CS202H Computer Hardware
• CS301A Computer Organization & Architecture
• CS312N Networking Principles & Architecture
• CS321O Operating Systems
• CS321P Programming Languages & Theory
• CS322A Algorithms & Complexity
• CS322E Software Engineering
• CS342D Database Management Systems
• CS351S Computer Security
• CS490I Internship
• CS492S Senior Seminar
• MA121 Calculus I
• MA122 Calculus II
• MA231 Linear Algebra
• MA253 Discrete Mathematics
• MA260 Elementary Statistics

Three units of the following:

• CH151 General Chemistry I (3)
• GS150 Essentials of Geology (3)*
• LS150 Essentials of Biology (3)*
• PS251 General Physics I (3)

*If not taken to satisfy general education science requirement.

Artificial Intelligence Emphasis Courses

Total units required for emphasis: 71

• CS361A Artificial Intelligence
• CS361M Machine Learning
• CS362N Natural Language Processing
• CS362V Computer Vision