Brown University
MS in Data Science (Online, Policy & Governance)
Last reviewed June 2026 by the AI Graduate editorial team. Program data is compiled and verified from official university sources — see our methodology.
How this program compares
At an estimated $60K in total tuition, the MS in Data Science (Online, Policy & Governance) sits about 41% above the $42.4K average for AI master's programs in our database — placing it in the 76th percentile on cost among the 531 we track at this level. It is one of the 57% of programs in our database offered fully or partly online.
Admission Snapshot
Typical admitted student: A bachelor's degree with a strong GPA (typically 3.0+), prerequisites in calculus, linear algebra, probability/statistics, and programming (Python/R), and relevant quantitative background are required.
About This Program
Brown University's online MS in Data Science with a Policy & Governance emphasis blends Ivy League data science training with the societal, ethical, and policy dimensions of AI and data. It reflects Brown's interdisciplinary, socially engaged academic identity.
The program suits professionals who want technical data science skills paired with the judgment to navigate governance, ethics, and public-policy contexts where data and AI increasingly intersect.
Why students choose it: Ivy data science training paired with a distinctive policy, ethics, and governance lens.
Career Outcomes
Lead as AI Ethics Specialist in Cross-Industry AI with machine learning expertise
- 1. Data Policy Analyst
- 2. Government Data Scientist
- 3. Privacy and Governance Specialist
- 4. Public Sector Data Strategist
What You'll Learn
- Analyze policy impacts using advanced data science methods.
- Evaluate ethical, legal, and governance frameworks for data usage.
- Apply machine learning to public policy and societal challenges.
- Communicate data insights to policymakers and stakeholders.
Curriculum Highlights
The curriculum features eight required courses delivered asynchronously, covering technical foundations, machine learning, and a final applied learning experience.
Top Employers
Top employers include government agencies like the FDA and Census Bureau, tech policy firms, consulting companies such as McKinsey, and international organizations like the World Bank.
Admissions
A bachelor's degree with a strong GPA (typically 3.0+), prerequisites in calculus, linear algebra, probability/statistics, and programming (Python/R), and relevant quantitative background are required.
Application Materials
- Statement of Purpose: Required (short-form questions on skills, goals, and program fit)
- Letters of Recommendation: 3
- Resume: Required
- Transcripts: Official transcripts required
Academic Requirements
- Degree Required: Bachelor's degree
- GRE/GMAT: Not Required
- TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)
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