The curriculum is built upon a fine combination of foundation courses in data science, computing, mathematics, statistics, and law, and is designed to provide students with advanced training in both theory and practice in Data Science and Engineering.

It is also unique in its emphasis on data privacy, ethical and legal issues for the data science profession, and privacy-preserving techniques. Students may also pursue a minor in a data-intensive field, thus bridging domain-specific knowledge with data science and engineering skills.

Curriculum Map

The programme offers graduates new and exciting career choices in the fastest-growing job positions like data engineer/architect, data scientist, data analyst, machine learning engineer, big data engineer, business analyst, and information security analyst. Below shows a summary of the skillsets required by data analyst, data scientist, and data engineer.

Curriculum Details

UG 5 Requirements (54 credits)

Engineering Core Courses (24 credits)

Discipline Core (Introductory) Courses: 30 credits

Discipline Core (Advanced) Courses: 18 credits

Discipline Elective Courses (30 credits)

Capstone Experience and Internship (12 credits)

Elective Courses (72 credits)

+Capstone Experience

Course Descriptions