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- Master of Business Administration (MBA) (Semester)
- Master of Healthcare Administration (MHA)
- MS in Cybersecurity (Quarter)
- MS in Data Science (Quarter)
- MS in Human Resource Management (Semester)
- MS in Industrial and Organizational (I/O) Psychology
- MS in Information Technology (Quarter)
- MS in Leadership (Quarter)
- Executive Master of Business Administration (EMBA)
- Master of Information Systems Management (MISM)
- MS in Accounting
- MS in Communication
- MS in Cybersecurity (Semester)
- MS in Data Science (Semester)
- MS in Information Technology (Semester)
- MS in Finance
- MS in Leadership (Semester)
- MS in Management
- MS in Marketing
- MS in Project Management
- MS in Software Engineering
- Master of Business Administration (MBA)
- MS in Human Resource Management
For students beginning their program November 28, 2022 or later.
The MS in Data Science program empowers students with the specialized skills needed to turn raw information into valuable business insights. Through courses developed in collaboration with IBM, students focus on:
- Using digital data and tools to analyze and ethically solve pressing problems in any organization or industry.
- Learning how to collect, analyze, and visualize data, and communicate insights to diverse stakeholders.
- Building practical, immediately applicable skills through interactive case studies, visualizations, and applications.
Walden’s MS in Data Science program is focused on responsible data management practices and the ethical use of data to address business challenges.
Learning Outcomes
Upon completion of the MS in Data Science, students will be able to:
- Evaluate emerging technical developments that apply to data science.
- Analyze current technologies that provide practical solutions to data science problems.
- Evaluate the role of supporting technologies for data science in data driven decision-making.
- Analyze legal, ethical, professional and social issue elements within the domain of data science.
- Differentiate how the techniques and tools of big data predictive analytics can be used to add “business value” in data driven decision-making in the modern work place.
Degree Requirements
- 45 total quarter credits
Curriculum
- Students may take this as a non-degree course.
Course Sequence
| Quarter | Course | Credits |
|---|---|---|
| Quarter 1 | MDSC 6005 - The Global Technology Environment | 5 credits |
| Quarter 2 | MDSC 6401 - Statistical Concepts for Big Data | 5 credits |
| MDSC 6245 - Big Data | 5 credits | |
| Quarter 3 | MDSC 6265 - Data Mining | 5 credits |
| MDSC 6685 - Data Visualization | 5 credits | |
| Quarter 4 | MDSC 6665 - Predictive Analytics for Decision Making | 5 credits |
| MDSC 6210 - Cloud Computing | 5 credits | |
| Quarter 5 | MDSC 6240 - Advanced Database Systems | 5 credits |
| MDSC 6190 - Foundations of Intelligent Systems | 5 credits |