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Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

This course will explore the intersections between machine learning (ML) and data systems. The first half of the course will cover modern methods of using ML to analyze unstructured data (images, video, audio, text). The second half of the course will cover the data systems used to manage the training and deployments of ML. This course will be research-oriented and discussion-based: most classes will be based on research papers. There will be a final project, which will either be: 1) a novel research contribution, 2) reproducing existing work, with thorough documentation, or 3) a synthesis of the literature in a final report and blog post. Prerequisites: CS 411 (databases) and CS 440 (ML). Or equivalent experience for both.