CMPT 311: Introduction to Artificial Intelligence (for Non-CS Majors)

This course introduces the fundamental ideas behind artificial intelligence and explores some of the latest and most exciting developments in the field. The goal is to give you a broad understanding of AI, how it works, how it is used in the real world, and some of its social implications.

CMPT 311 is designed for students with a good technical background and basic Python knowledge who want to learn about AI but don’t necessarily plan to take more advanced AI courses. Students from both computing and non-computing disciplines are welcome, as long as they meet the course prerequisites!

CMPT 311 vs CMPT 310

If you are wondering how CMPT 311 compares to CMPT 310, the following visualization could help you.

Everything a CS undergraduate specializing in AI learns
CMPT 310
The rest of the AI concentration curriculum (e.g., CMPT 410, CMP 420, etc.)
CMPT 311
An overview of the key AI concepts, along with selected topics from more advanced AI courses, with a more applied intent.

Tentative outline

  • Introduction to AI
  • Classical AI (Agents, Search, Knowledge Representation, and Probabilistic Reasoning)
  • Machine Learning
  • Neural Networks and Deep Learning
  • MDPs and Reinforcement Learning
  • Language Models and Transformers
  • LLMs and LLM-Based Systems
  • Vision, Multimodal, and Generative AI (time permitting)
  • Society, Governance, and Future Directions

Course Times + Location (Spring 2027):

  • Wednesdays, 1:30–2:20 pm, Room C9002,
  • Fridays, 12:30–2:20 pm, Room WMC3520.

Prerequisites

  • CMPT 225, (MATH 232 or 240), and (STAT 270 or equivalent), all with a minimum grade of C-.

Grading

  • Grades will be discussed in the first week of class.

Textbook

  • Artificial Intelligence: A Modern Approach, 4th edition Stuart Russell, Peter Norvig, Pearson, 2021, ISBN: 9780137505135.

Teaching Team

- More information about the course, including the syllabus, schedule, and assignments, will be posted here in the coming weeks.