Minor in Data Science

JI offers a minor in Data Science to provide students with a basic understanding in those aspects of computer science, statistics, and mathematics that are relevant for analyzing and manipulating large complex datasets. A minimum of 15 credits of courses are required for this minor, including:

Core (required) Courses (8 credits)

• Ve401 Probabilistic Method in Engineering (4 credits)

• Ve414 Bayesian Data Analysis (4 credits)

Elective Courses: at least two out of

• Ve406 Applied Regression Analysis using R (4 credits)

• Ve445 Introduction to Machine Learning (4 credits)

• Ve484 Data Mining (4 credits)

• Ve488 Data Mining and Machine Learning (4 credits)

• Ve492 Artificial Intelligence (4 credits)

• Ve501 Random Processes (4 credits for undergraduate students, 3 credits for graduate students)

• Ve472/572 Methods and Tools for Big Data (3 credits)

• Ve485 Optimization of Machine Learning (3 credits)

• Ve581 Convolutional Neural Networks for Visual Recognition (3 credits)

• Ve593 Problem solving with AI techniques (3 credits)

More courses may be added to this list with prior approval, such as AI and machine learning


– Sophomore standing and above
– Having declared a major
– In good academic standing

If planned well in advance of the senior year, the program should not add to the credits required for a bachelor’s degree at JI. A student should receive a grade of C or better for all the courses required for the minor. The Minor in Data Science should be declared before graduation. Transfer credits are acceptable for the Elective courses. No credits may be used to satisfy the requirements of more than one minor. No credits may be double counted for a minor and an undergraduate research certificate.