- Redirects Breadcrumbs to Main Page
- 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 prior to November 28, 2022.
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
- 30 total semester credits
Curriculum
Course Sequence
The recommended course sequence is as follows:
| Semester | Course | Credits |
|---|---|---|
| Semester 1 |
DSCI 6005 - The Global Technology Environment |
3 semester credits |
|
DSCI 6655 - Data Warehousing and Business Intelligence |
3 semester credits | |
| Semester 2 |
DSCI 6401 - Statistical Concepts for Big Data |
3 semester credits |
|
DSCI 6245 - Big Data |
3 semester credits | |
| Semester 3 |
DSCI 6265 - Data Mining |
3 semester credits |
|
DSCI 6685 - Data Visualization |
3 semester credits | |
| Semester 4 |
DSCI 6665 - Predictive Analytics for Decision Making |
3 semester credits |
|
DSCI 6210 - Cloud Computing |
3 semester credits | |
| Semester 5 |
DSCI 6240 - Advanced Database Systems |
3 semester credits |
|
DSCI 6190 - Foundations of Intelligent Systems |
3 semester credits |