UWaterloo CS 886
FreeRecent Advances on Foundation Models.
FreeFree tier
About UWaterloo CS 886
CS 886 is a graduate-level course offered at the University of Waterloo's Cheriton School of Computer Science, focusing on recent advances in foundation models, including large language models, multimodal models, and their applications. The course is instructed by Dr. Wenhu Chen and includes weekly lectures, student pair presentations (80 minutes each), reading notes on recent papers, and a course project requiring an 8-page report and a final presentation. Topics span foundation model history, RNNs, CNNs, natural language processing, and computer vision. The course uses Piazza for communication and LEARN for submissions. It is designed for graduate students with a background in deep learning.
Key Features
Instructor-led lectures on foundation models, RNNs, CNNs, NLP, and CV
Student pair presentations (80 minutes) on selected topics
Reading notes submission on recent deep learning papers
Course project with 8-page report and final presentation
Use of Piazza for communication and LEARN for submissions
Winter 2024 term schedule with weekly sessions
Pros & Cons
Pros
- Covers cutting-edge topics in foundation models and their applications
- Structured curriculum with hands-on project and presentations
- Opportunity to engage with recent research through reading notes and discussions
- Taught by a domain expert with active research in multimodal foundation models
Cons
- Requires prior knowledge of deep learning and neural networks
- Limited to enrolled University of Waterloo graduate students
- Fixed schedule during Winter 2024 term only
- No public access to course materials outside enrolled students
Best For
Graduate-level education in AI and machine learningUnderstanding and researching foundation modelsPreparing for research in large language models and multimodal AIAcademic credit and project experience for University of Waterloo students