Course Schedule and Catalog
Course Schedule - Spring Semester 2027
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
Meeting location information can now be found on student schedules in ESTHER (for students) or on the Course Roster in ESTHER (for faculty and instructors).Additional information available here.
COMP 346 001 (CRN: 26692)
INTRO TO AI
Long Title: INTRODUCTION TO ARTIFICAL INTELLIGENCE
Department: Computer Science
Instructor: Unhelkar, Vaibhav
Meeting: 9:25AM - 10:40AM TR (11-JAN-2027 - 23-APR-2027)
Part of Term: Full Term
Grade Mode: Standard Letter
Course Type: Lecture
Language of Instruction: Taught in English
Method of Instruction: Face to Face
Credit Hours: 3
Course Syllabus:
Course Materials: Rice Campus Store
Restrictions:
Must be enrolled in one of the following Level(s):
Undergraduate Professional
Visiting Undergraduate
Undergraduate
Prerequisites: COMP 215 AND STAT 315 AND COMP 282
Section Max Enrollment: 73
Section Enrolled: 0
Enrollment data as of: 2-NOV-2026 8:32AM
Final Exam: Scheduled Final Exam-OTR Room
Description: No subject unleashes the spirit of innovation like artificial intelligence (AI). Think of companies
like Deep Mind, OpenAI, Google, Hugging Face, and technologies like speech recognition, language translation, question answering systems, autonomous driving, household robots, chatbots, text-to-image generators, each of which embodies core algorithms in AI. COMP 346 offers an introduction to AI, which is the discipline of designing agents that make decisions and solve problems in the real world. The course covers the mathematical and computational concepts needed to design, engineer, and evaluate AI agents that do the right thing in the face of limited computational resources and limited information. The course draws on computer science, probability theory, statistics, optimization, game theory, logic, and decision theory.
COMP 346 is a required course for the AI major. It can also be taken as part of a general education in computer science, as grounding for future research in AI, or to gain familiarity with AI algorithms for application in other fields.