Curriculum
Degree Requirements
The MDATA program requires completion of 30 total credit hours, distributed as follows:
- Two specialized graduate certificate tracks (each ~12 credits)
- Two capstone courses (6 credits total)
Students are individually responsible for meeting coursework requirements. Students should ensure that they are aware of all requirements and initiate resolution of any apparent inconsistencies. MDATA students are required to maintain at least a 3.0 GPA for degree-program courses. Grades of C- or lower will not be accepted. Modifications or substitutions for the listed MDATA course requirements can be made with department approval.
Here are some important requirements and details to keep in mind:
- At least 18 credits of the 30 credits must be 6000-level courses per USU Graduate School requirements.
- Most advanced courses require skills in Python (DATA 6500) and Database (DATA 6300). Plan to take these courses prior to entering the program or in your first semester.
- Students in the face-to-face program can take online courses. Face-to-face students should be aware that the tuition amount for online courses is different, see the Tuition Overview.
- Course substitutions can be made within certificate tracks or among the 2 capstone courses (6 credits) with approval from the academic advisor.
- A given course cannot be used to complete more than one certificate, or both a certificate and a capstone credit requirement.
Post-Baccalaureate Certificates
The Machine Learning Operations (MLOps) certificate prepares students to deploy, manage, and scale machine learning models in production environments.
The FinTech Analytics certificate equips students with advanced analytical and computational skills for the rapidly evolving financial technology industry.
The Marketing Analytics certificate focuses on using data-driven insights to drive strategic marketing decisions.
The Tech Innovation and Entrepreneurship certificate empowers students to develop, prototype, and scale innovative technology-based ventures.
The Accounting FinTech certificate blends accounting expertise with data analytics and emerging financial technologies.
Programming, machine learning and artificial intelligence, visualization, and data mining using the latest technologies.
Data Science is an interdisciplinary field that includes the management, analysis, and visualization of data to make the best possible evidence-based decisions, and draws primarily from the fields of Statistics and Computer Science.
Machine learning and artificial intelligence (AI) are at the forefront of technological advances in fields such as healthcare, finance, autonomous vehicles, and more.
multidomain approach to anticipating threats and opportunities emerging from the world's increasingly complex security environment.
MDATA Capstone Courses (6 Credits)
Select 2 courses, for a total of 6-credits.
| Credits | Course Number | Course Name | Semester Taught |
|---|---|---|---|
| 3 | IS 6100 | Agile Tech Design & Development | Fall, Spring |
| 1-6 | IS 6250 | Graduate Internship | Fall, Spring, Summer |
| 3 | DATA 6570 | Building Software with AI | Fall, Spring |
| 3 | DATA 6910 | Data Competitions and Problem Solving | Fall, Spring |