Study Plan

MSDS Study Plan

The six foundational classes expose students to the identification of questions whose answers can be aided by data retrieval, data cleaning and data modeling tools, plus specialized algorithmic and statistical processing, machine learning, pattern recognition and interactive visualization tools. A faculty supervised CapStone class is dedicated to building prototype systems where students exercise the skill set acquired in the other foundational classes.

The six remaining elective courses offer students the opportunity of further specializations in Statistics, Algorithms, Optimization, Machine Learning, Data Privacy/Security, Computer Graphics and Vision. An elective second Capstone project can be used, at the student's discretion, to compete in a Master wide context in Data Science.