Data Analytics, B.A.S./B.S.

Professors: Cheryl Beaver, Scott Beaver, Hamid Behmard, Laurie Burton, Breeann Flesch, Jie Liu, Becka Morgan, Scot Morse

Associate professors: Matthew Ciancetta, Matthew Nabity, Thaddeus Shannon

Assistant professors: Lucas Cordova, Ben Coté, Leanne Merrill

Mission

The Data Analytics program prepares students to thrive in the constantly evolving field of working with big data. The field is interdisciplinary by nature and is built on a foundation of Mathematics, Computer Science, Information Systems and Data Analytics courses. This program emphasizes the applied practice of data analytics techniques for solving problems in the real world.

Learning Outcomes

Use relevant technology for the analysis of large, complex, or messy data sets to design, implement, and evaluate analytics-based solutions.
Use quantitative information in connection with the argument or purpose of the work, presents it in an effective format, and explicates it with consistently high quality.
Collect, analyze and assess evidence to reach informed conclusions and judgments.

Core Courses

Choose One Concentration

Total Credits 75-92

Note

Data Analytics students must have a grade of C or better in courses that are used to satisfy the major requirements. Students must also have a C or better in all listed prerequisite courses unless waived by the course instructor and the computer science division chair.

Satisfactory Grade Use

Only Earth Science (ES) courses used in the DA: Geographic Information Systems Concentration and DATA 101 Foundations of Data Analytics may be fulfilled with a grade of S.
No other program requirements may be fulfilled with a grade of S.
Do not select Satisfactory/No Credit grading for any other courses that will be used in the program.