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The Master of Science in Data Science (MSDS) at Michigan State University is a fully online, interdisciplinary, and STEM-designated program designed to provide students with the technical, analytical, and communication skills necessary to transform data into actionable insight. Offered jointly by the College of Engineering, College of Natural Science, and College of Business, the MSDS program integrates computer science, statistics, data engineering, and domain applications to meet the evolving needs of the data economy.
With a flexible, online format, the program caters to both full-time students and working professionals, preparing them to succeed in fields such as tech, finance, healthcare, agriculture, and government.
Program Format & Duration
100% online with asynchronous course delivery
Can be completed in 20–28 months (part-time or full-time)
Fall and Spring start options
STEM-designated (OPT eligible for international students studying from the U.S.)
No GRE required
Core Curriculum Components
The MSDS curriculum requires completion of 30 credit hours across foundational, computational, and application-focused areas.
Core Areas
Computing Foundations
Introduction to Programming for Data Science
Data Structures and Algorithms
Database Management and Big Data Tools
Mathematics & Statistics
Probability and Statistics for Data Science
Applied Linear Algebra
Statistical Modeling and Inference
Machine Learning & AI
Introduction to Machine Learning
Advanced Topics in AI or Deep Learning
Data Mining and Pattern Recognition
Data Engineering & Visualization
Data Wrangling and Transformation
Cloud-Based Data Processing
Data Visualization and Communication
Capstone Project
A real-world data science project integrating technical, analytical, and business-facing skills
Completed in the final semester with guidance from MSU faculty and/or industry mentors
Despite being fully online, MSU’s MSDS program ensures practical, hands-on learning through project-based coursework, capstone projects, and collaborative problem-solving.
Capstone Project
The capstone experience simulates industry work, with students:
Identifying a real-world data challenge
Collecting, cleaning, and modeling data
Using ML or statistical methods to drive predictions
Creating dashboards or reports to communicate findings to stakeholders
Capstone topics have included:
Retail demand forecasting
Fraud detection in banking
Health outcome prediction
Social media sentiment analysis
Agricultural yield optimization
Industry-Relevant Tools & Platforms
Students gain proficiency in:
Python, R, SQL
Spark, Hadoop, and cloud computing (AWS, Azure)
TensorFlow, Scikit-learn, Keras
Power BI, Tableau, Matplotlib, Plotly
GitHub, Docker, Jupyter Notebooks
Optional Networking Opportunities
While remote, students benefit from:
Virtual career panels and alumni talks
Access to MSU’s Handshake career platform
Online workshops in technical interviews and resume-building
Collaboration with faculty affiliated with MSU’s Center for Business and Social Analytics
Graduates of the MSU MSDS program are prepared to take on technical, strategic, and research-driven roles across a wide range of industries. The program’s interdisciplinary structure ensures that graduates can work across domains, from tech and business to public policy and science.
Career Outcomes
Common job titles include:
Industries Hiring MSDS Graduates
Graduate Study & Advancement
Some students continue on to:
Salary Overview-
Top Employers-
Geographic Placement-
Industry Sectors-
Career Growth and Progression-
What This Means for You-
Bachelor’s Degree: Hold a four-year bachelor’s degree in a relevant quantitative discipline from a recognized institution. Transcripts: Upload unofficial (with official transcripts sent directly by institutions) copies from all undergraduate and graduate institutions attended. Letter of Motivation: Submit a two‑page combined personal and academic statement outlining your interest in data science and career goals. Letters of Recommendation: Submit at least three letters of recommendation directly from referees.English Proficiency: International applicants whose education was not in English must provide TOEFL, IELTS, or equivalent scores per university requirements. GRE Scores: GRE is optional and may be submitted to strengthen the application.Technical Background Survey: Complete a post-application technical background survey (sent automatically) required for full consideration.Priority Deadline: Apply by January 15, 2025 for priority consideration; applications submitted up to March 15, 2025 will be accepted on a rolling basis.Three-Year Bachelor’s Degree: MSU normally does not accept three‑year bachelor’s degrees as equivalent to a U.S. four-year degree, unless a formal waiver (including documentation and department approval) is granted WES Evaluation: If you request a waiver for a three-year degree, MSU’s Graduate School and department will likely require a credential evaluation (e.g., WES) to assess U.S. equivalenceData AnalystData ScientistBusiness AnalystStatisticianStatistical ProgrammerSAS ProgrammerMachine Learning EngineerDeep Learning EngineerAI ResearcherData EngineerBI DeveloperData ArchitectAnalytics ConsultantAdvisory ConsultantQuantitative AnalystRisk AnalystOperations AnalystMarketing AnalystResearch ScientistInsights AnalystForecasting AnalystHealthcare Data AnalystFinancial Data AnalystProduct Analyst
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