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Spring 2020 Computer Science W4995 section 013
TOPICS IN COMPUTER SCIENCE
CAUSAL INFERENCE DATA SCIENCE

Call Number 20029
Day & Time
Location
W 7:00pm-9:30pm
834 Seeley W. Mudd Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Adam Kelleher
Type LECTURE
Method of Instruction Classroom
Course Description Prerequisites: any introductory course in statistics.
This course introduces fundamental machine learning models, such as logistic regression, decision trees, ensemble algorithms, support vector machine, and clustering analysis, with special emphasis on their learning capacity to solve financial problems. Some of the financial applications explored are algorithmic trading, portfolio optimization, and risk management. This hands-on course, with practical exercises based on Python, is appropriate for students from economics, business, science, and engineering interested in machine learning and finance.
Web Site Vergil
Department Computer Science
Enrollment 34 students (42 max) as of 3:39PM Tuesday, March 31, 2020
Subject Computer Science
Number W4995
Section 013
Division Interfaculty
Open To Architecture, Schools of the Arts, Barnard College, Columbia College, Engineering:Undergraduate, Engineering:Graduate, GSAS, General Studies, SIPA, Journalism
Campus Morningside
Section key 20201COMS4995W013

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SIS update 03/31/20 15:39    web update 03/31/20 21:19