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CMPT 983 G200 Special Topics in Artificial Intelligence

Type
Graduate Studies and Professional Development
Institution
SFU
Professor / Instructor
Li, Ke
Dates
Sept 8- Dec 1, 2021

This course covers the fundamentals and applications of generative models, a branch of machine learning focused on learning unknown probability distributions from observed examples. Generative models are used to automatically generate complex data such as images, text and sound from limited user input, simulate alternative possible outcomes that are not observed in the real world, generate multiple possible predictions when the input cannot uniquely determine the output, quantify the amount of uncertainty in the model prediction and incorporate domain knowledge into otherwise uninformed domain-agnostic algorithms. Both classical approaches and modern techniques developed within the last 10 years will be covered, and their applications to different areas of artificial intelligence, such as computer vision, natural language processing and audio processing will be highlighted. The goal is to provide students with a comprehensive understanding of the latest techniques and bring them up to speed on the current scientific literature. By the end of the course, students will understand when generative models should be applied and how they can be applied in the context of their own research.

You are applying for a $500 scholarship towards a qualifying course at one of our post-secondary education partners: BCIT, Northeastern University, SFU or UBC. Applicants must be either Canadian Citizens, BC permanent residents or working towards obtaining one of these.

Please only apply for this scholarship once you have been enrolled or waitlisted in an applicable course. We will be confirming all student details with instructors.

Apply for Scholarship

To be eligible for this scholarship, you must be a woman (or identify as a woman), and currently live in BC, Canada. Do you meet both of these criteria?