Data Science and Analytics: Advanced Project Course

The project course explores leading-edge trends in data science and analytics at Silicon Valley and tech firms, at the doctoral and masters level of research.

The topics covered will include (a subset of):

• Data analytics and “Big Data”
• Machine learning and scalability
• Business analytics including online marketing and advertising, financial services and risk analytics, operational and service analytics
• Information retrieval (search)
• Information extraction
• Social networks and social media
• Healthcare analytics
• Energy analytics

The course and projects will cover the exploration of leading edge analytics, data mining, and machine learning techniques at Silicon Valley firms in a research project mode, with associated readings and final report and paper.

This requires project work based on strong mathematical training and prior exposure to data mining, analytics, machine learning, optimization, statistics, stochastic modeling, and/or economics (Minimal level: One or more representative analytics courses such as EECS 281A/STAT 241A, Info 240, Info 271B, EECS 227A, CS 188/189, CS 288, EE 227A, EE226A, EE 229, IEOR 262A, IEOR 263A, Econ 240A.)