BS-MS: Data Science
Student Learning Outcomes
Students graduating from this program will:
- develop solutions for advanced problems using appropriate skills and knowledge in data science;
- recognize and apply state of the art techniques and tools in the data science field;
- work effectively in teams;
- demonstrate advanced knowledge in data science.
Admission requirements
- 3.0 undergraduate cumulative GPA and
- Undergraduate degree in Computer Science or Information Technology
| Code | Title | Credits |
|---|---|---|
| Core Requirements | ||
| COMP-SCI 5530 | Principles of Data Science | 3 |
| COMP-SCI 5540 | Principles of Big Data Management | 3 |
| COMP-SCI 5565 | Introduction to Statistical Learning | 3 |
| COMP-SCI 5567 | Deep Learning | 3 |
| COMP-SCI 5588 | Data Science Capstone | 3 |
| Electives: | 15 | |
| Cloud Computing | ||
| Big Data Analytics and Applications | ||
| Advanced Software Engineering | ||
| Knowledge Discovery and Management | ||
| Information Security and Assurance | ||
| Computer Vision | ||
| Special Topics | ||
| Directed Readings | ||
| Mathematical Methods in Data Science | ||
| Business Analytics and Statistics | ||
| Data Management and Data Mining for Business Analytics | ||
| Predictive Analytics Using R | ||
| Statistical Design Of Experiments | ||
| Time Series Analysis | ||
| Total Credits | 30 | |
Five Year Program Sample
Students should follow the sample program as listed for the BS in Data Science degree and should apply for the graduate degree prior to enrolling for the fall semester of their fourth year. During their fifth year, they could enroll in 12 credit hours each semester or make use of the summer semester between their fourth and fifth year to take a course or special project, if offered.
For additional details, please contact our Department by e-mail mailto:sse@umkc.edu.