Really enjoyed this course mainly due to the professor. Mehrdad was always enthusiastic and taught in a way that was very iclicker heavy but really supported learning. There were weekly assignments (around 6 hours each) that you could work on with a partner. There were 2 midterms, a final, and these assignments. The topics all related to each other and gives you an understanding of the building blocks that lead to predictive models. I didn't feel like I was learning about "AI" as we know it today with LLMs however its clear this course is providing very solid base for 422 to build on.

Lots of search problems. Then lots of probability.

Amazing professor. Always excited to learn and answer questions. You could really tell that he cares about his students!

Even though assignments don't take a super long time its important to start them early because doing them without the help of AI really adds to your learning. Practice questions for the midterms are very conceptual and not calculation/example based at all (this threw me off a bit) but the exams weren't that difficult if you had good conceptual understandings of the concepts.

Course had some interesting content but was not what I was expecting. I'd recommend NOT taking this course and take CPSC 340 or 330 instead. The whole month and a half was just learning different graph search algorithms and second half was just probability, all of which you could self study. There was a lot of content as well but the exams were super straight forward and fair and had few trick questions.

Know your graph and data structures from CPSC 221 and it was much easier that I took Math 302 (probability) beforehand, making the second part of the course easier than if I hadn't taken it.