CSE 780 / Data Science

Cross-listed as STATS 780

Prerequisite(s): Registration in a graduate program in the Faculty of Science, Health Sciences or Engineering or permission of the instructor.

The course will cover core and selected topics in data science. The core topics are classification and regression trees, neural networks, boosting, bagging, unsupervised learning, signal processing, random forests, ensemble methods, data visualization, big data, and data storage. Selected topics include data warehousing, data compression, data cleaning, deep learning, and artificial intelligence.