Mechanical & Industrial Engrg 622 - PredictvAnalytics&StatLearning

Data analytics, statistical/machine learning, and predictive modeling are now used widely in all fields. The purpose of this course is to provide introductory knowledge that will help students understand the fundamentals of the field and use software packages to solve problems. The emphasis will be on applying the statistical methods to real data sets. The 600-level class will require students to explore topics in more depth. The computational assignments, which comprise 65% of the course, will test advanced concepts in statistical learning and predictive analytics in the higher-level offering.

Open to graduate students in Engineering Management and Industrial Engineering & Operations Research only. Graduate students in other majors must request instructor permission to be enrolled.

Pre-requisites: Basic knowledge of Calculus, Linear Algebra, Probability and Statistics, and Programming/Problem-solving with Computers. Python and/or R will be heavily used; either some experience or true willingness to learn it is a must. Resources will be provided to support students. Please contact the instructor if you have any questions or concerns.