Computational and Data SciencePrograms of Study
Developing mathematical models, employing numerical methods, and using data visualization have become increasingly important for a variety of businesses and industries. The Computational and Data Science Track incorporates coursework to reflect the breadth of computational and data science employed to solve real-world problems.
There are two focus areas within the Track:
- Computational Science
- Data Science
Graduate Students in the Computational and Data Science Track take advanced science, math, and engineering courses within these two focus areas and choose electives based on their professional goals.
Students complete a minimum of 36 credits of graduate-level course work.
15 credits of STEM graduate-level course work in one of the two focus areas are required
Computational Science |
Data Science(Aligned with the School of Computing's Graduate Certificate in Data Science) |
Core Courses (3 required):MATH 6805 (or 5010) Introduction to Probability MATH 6860/6865 Introduction to Numerical Analysis I, II MATH 6610/6620 Analysis of Numerical Methods I, II Electives (2 required):CS 6269 Programming for Engineers Graduate-level courses from the Department of Mathematics or from the School of Computing Example programs of study can be found here |
Core Courses (Must take at least three of the following)CS 6140 Data Mining Get up to Speed (optionally take one)COMP 5005 Programming for Engineers Electives
|
Advanced Quantitative Skills (6 credits)
MST 6600 Applied Statistical Techniques
CS 6630 Visualization for Data Science
CS 6269 Programming for Engineers
MATH 5600 Survey of Numerical Analysis
MATH 5740 Mathematical Modeling
MATH5750 Topics in Applied Mathematics
MATH 6820 Time Series Analysis
STAT 6003 Survey of Statistical Computer Packages
STAT 6571 Foundations of Applied Data Analytics and Visualization
STAT6573 Practical Data Science
Transferable Skills (12 Credits)
MST 6100 —Policy and Regulatory Considerations for Scientist and Engineers
(3 credits)
MST 6110 Business Development for Scientist and Engineers
(3 credits)
MST 6200 Professional Development for Scientist and Engineers
(3 credits)
MST 6210 Operations and Project Management for Scientist and Engineers
(3-credits)
electives: students can request to take 3-credits of graduate coursework from the David Eccles School of Business or an approved elective (contact program director for a list of transferable skills electives)
Professional Experience Project (Internship; 3 Credits)
An essential component of the PMST degree is a Professional Experience Project (internship) working with a local company, government agency, or non-profit organization. These activities engage students in real-world work situations involving technical problems, teamwork, communication skills, and decision-making.
Notes: Course availability is subject to change. Substitute classes may be taken upon approval. Courses may have pre-requisites which are published in the University Course Catalog; students are responsible for confirming they meet course requirements and pre-requisites.