Stand out in the career search with an advanced degree in data science—one of the hottest career fields in the world. If you are an undergraduate student with a major, minor, or specialization in data science, you can earn a master’s degree in just one additional year.
The 4+1 program saves you time and money. You’ll take up to nine fewer credit hours than if you earned a B.S. and M.S. separately. And you’ll be enrolled in some graduate courses while paying the undergraduate rate.
The program is designed so that highly motivated students can earn a master’s degree in just one additional year. To do that, you’ll take at least one graduate-level course during your senior year, when you’re still classified as an undergraduate. You need to request permission from your advisor.
You’ll be classified as an undergraduate through the last semester you are enrolled in undergrad requirements. You have to complete at least 21 hours of coursework while classified as a grad student.
For the semesters you are in graduate status, you will pay the same tuition and fees as other M.S. students.
Transitioning to graduate student status may affect any undergrad scholarships or other funding you have. Make sure to check on this and plan for it.
You’ll receive your B.S. and M.S. simultaneously after you’ve completed both degrees.
Students in this program are required to complete 12 credit hours of core coursework that covers three credit hours of Statistical Methods, three credit hours of Data Management and Engineering, three credit hours of Machine Learning, Data Mining, and Text Mining, and three credit hours of capstone project. The nine remaining credit hours are for electives to best suite your individual interests, needs, and overall career goals.
Select one course from the following:
Select one course from the following:
Select one course from the following:
Students will be required to work on a project that applies the knowledge and skills learned to solve real-world problems for a company, organization, or individual. This may be fulfilled through a capstone course, an internship, or an independent study project. The aim of this requirement is to demonstrate students' capabilities to prospective employers and inspire innovation.
The remaining nine credit hours are selected from additional data science-related course offerings within the Luddy School of Informatics, Computing, and Engineering. Students may not earn credit for courses taken to fulfill the core or capstone requirements.
This sample degree map shows a path a typical student can take after completing the 120 credits required for an undergraduate degree.
| Semester | Elective | Credits |
|---|---|---|
| Summer | Elective | 3 Credits |
| Fall | 2 Core | 9 Credits |
| Spring | 1 Core | 9 Credits |
