UMass Amherst Computer Science in Boston: Machine Learning 589

 The College of Information and Computer Sciences at the University of Massachusetts is pleased to offer its first class at the university's new Boston location at One Beacon St. This course is geared towards UMass and non-UMass graduate students seeking to complete coursework towards their degrees, and computer science professionals who want to build skills in this growing field.

Time & Location

The course will be held on Mondays from 6 to 9 pm starting on January 25, 2016 at 1 Beacon Street, Lower Level, Boston, MA 02108.

Course Description

This course will introduce core machine learning models and algorithms for classification, regression, clustering, and dimensionality reduction. On the theory side, the course will focus on understanding models and the relationships between them. On the applied side, the course will focus on effectively using machine learning methods to solve real-world problems with an emphasis on model selection, regularization, design of experiments, and presentation and interpretation of results. The course will also explore the use of machine learning methods across different computing contexts including desktop, cluster, and cloud computing. The course will include programming assignments, a midterm exam, and a final project. Python is the required programming language for the course. Students are expected to have an undergraduate background in computer science.

Instructor

Dr. Rukmini Vijaykumar is an independent consultant in the Greater Boston area.   Current interest areas include data modeling and analysis, statistical inference, machine learning, and performance optimization. She served as Senior Member of Technical Staff at Verizon Communications in Waltham, MA developing automated systems for network fault diagnosis. Prior to that she was a Principal Engineer at MAK Technology working on AI-based research projects. She was an Assistant professor of Computer Science at the University of Southern Maine (1988-1992) where she taught undergraduate and graduate courses in Computer Science and served as the primary resource for AI-based projects and courses. She earned her Ph.D. in Computer Science from UMass Amherst (1989) in Robotics and AI, M.Tech. Computer Science and M.Sc. Mathematics from the Indian Institute of Technology, Madras, and B.Sc. in Mathematics from University of Madras.