Teaching Artificial Intelligence at Uppsala University 🤖
This September, I am honored to return to Uppsala University as a lecturer for Artificial Intelligence (1DL340), with 173 students taking the course this year.
Coming back to teach at the university where I completed my PhD is especially meaningful to me. Teaching a class of this size is both exciting and demanding, and I am grateful for the opportunity to share my knowledge, meet a new group of students, and work closely with the teaching team as we explore the foundational ideas and practical challenges of artificial intelligence.
Course Overview
Artificial Intelligence is a Master’s-level course worth 5 credits. The course examines how computers can solve problems that require more than straightforward computation, bringing together methods for search, reasoning, decision-making, uncertainty, and learning.
The main topics include:
- Heuristic search — using informed strategies to explore large problem spaces efficiently
- Adversarial search — reasoning and decision-making in competitive environments
- Planning and scheduling — constructing actions and allocating resources to achieve goals
- Bayesian networks — representing and reasoning with probabilistic dependencies
- Markov models — modeling systems whose behavior evolves under uncertainty
- Natural computation — solving problems through computational ideas inspired by natural processes
Together, these topics give students a broad foundation for understanding how AI systems represent knowledge, evaluate alternatives, and make decisions.
Teaching Team
I am delighted to teach the course together with Justin Pearson.
We are also joined by Olle Gällmo as Guest Lecturer. The course is hosted by Maria Andreina Francisco Rodriguez.
This year’s course is supported by five Teaching Assistants: Diletta Goglia, Jingwei Hu, Kristoffer Norrman, David Lide, Gouri Hariharan. Their work is essential in supporting exercises, answering questions, and helping students engage with the course material.
