Data-Driven Decision Making (Gr. Cert.) (15 credits)
Offered by: Technology & Innovation
Program credit weight: 15
Program Description
The 15-credit Graduate Certificate in Data-Driven Decision Making is designed to provide the fundamentals of computational intelligence focusing on leadership roles in increasingly digital organizations operating in the numerous fields that need to make data-driven decisions such as digital healthcare, maintenance of critical infrastructure, or dynamic supply management. The program is offered online with synchronous course activities.
Note: For information about Fall 2025 and Winter 2026 course offerings, please refer to Visual Schedule Builder. A technical issue is causing the "Terms offered" field to incorrectly report "this course is not currently offered" for many courses in the Course Catalogue.
Required Courses (9 credits)
| Course | Title | Credits |
|---|---|---|
| CCCS 640 | Applied Decision Science. | 3 |
Applied Decision Science. Terms offered: this course is not currently offered. Analysis of concepts, tools, and techniques provided by mathematical and computational sciences for decision making in its diverse formats. Examination of decision science techniques and their applicability. | ||
| CCCS 650 | Applied Data Science. | 3 |
Applied Data Science. Terms offered: this course is not currently offered. Analysis of techniques provided by statistics and computational sciences for machine learning and data science. Examination of real-world applications. | ||
| CCCS 660 | Computational Intelligence. | 3 |
Computational Intelligence. Terms offered: this course is not currently offered. Analysis of tools provided by mathematical and computational sciences for artificial intelligence as well as an examination of the numerous contexts in which computational intelligence can be applied. | ||
Complementary Courses (6 credits)
6 credits selected from:
| Course | Title | Credits |
|---|---|---|
| CCCS 670 | Information Visualization. | 3 |
Information Visualization. Terms offered: Summer 2025 Examination of the application of computational and mathematical concepts, tools, and techniques to visualize quantitative multi-dimensional information. Qualitative information in static, animated, and interactive digital formats. Guidelines and best practices from cognitive psychology, UX, and graphic design, including dashboard tools and storytelling methods. | ||
| CCCS 680 | Scalable Data Analysis. | 3 |
Scalable Data Analysis. Terms offered: this course is not currently offered. Concepts, tools, and metrics related to scaling up data analysis to handle massive amounts of data. Examination of methods for enabling technologies and applications such as big data and cloud computing. | ||
| CCCS 690 | Applied Computational Research. | 3 |
Applied Computational Research. Terms offered: this course is not currently offered. Analysis of a real-world case study of choice. Examination of version-controlled repositories and project management tools for tracking the tasks. Identification, formulation, and application of data-driven projects in areas of interest. | ||
Or another 600-level course offered by the School of Continuous Studies and approved by the academic unit.