Overview
The Data Science programme at the University of Minnesota provides a rigorous academic foundation for students aiming to excel in the rapidly evolving field of big data and analytics. This master's degree integrates theoretical knowledge with practical application to prepare graduates for complex technical challenges. Students engage with state-of-the-art methods that form the basis for next-generation computing technologies.
Why Data Science at University of Minnesota?
Choosing this programme means joining a collaborative environment supported by the College of Science and Engineering and the Data Science Initiative. The curriculum is uniquely interdisciplinary, drawing expertise from the Department of Computer Science and Engineering, the School of Statistics, and the School of Mathematics. Students benefit from access to high-performance computing facilities and a dedicated graduate faculty leading research in the field.
Tuition Fee Breakdown
- International fee: USD 16776 per semester
- National fee: USD 16776 per semester
- Local fee: USD 10632 per semester
Visit the Fees and Funding section for a breakdown in your local currency.
Syllabus
The curriculum is structured around three core focus areas: statistics, algorithmics, and infrastructure and large-scale computing. Students can choose between a Plan B track, which includes a faculty-guided capstone project, or a Plan C coursework-only track. Modules may include:
- Statistics
- Algorithmics
- Infrastructure and Large Scale Computing
- Data Science Capstone
- Big Data Analysis
- Data Science
Careers with Data Science
Graduates from this programme are equipped for high-level technical roles across various industries that rely on data-driven decision-making. The University provides extensive post-graduate career statistics and resources to help students transition into professional roles. Common career paths include positions in data engineering, machine learning, and advanced data analysis within both the public and private sectors.
Programme Structure
Courses include:
- Theory of Statistics
- Applied Regression Analysis
- Machine Learning
- Distributed Systems
- Data Mining
- Parallel Computing: Architectures, Algorithms, and Programming
Key information
Duration
- Full-time
- 24 months
Start dates & application deadlines
- Starting
- Apply before
-
Language
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Credits
Delivered
Campus Location
- Minneapolis, United States
Disciplines
Data Science & Big Data View 471 other Masters in Data Science & Big Data in United StatesWhat students do after studying
Academic requirements
English requirements
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- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- A four-year bachelor's degree from an accredited college or university in computer science, math, statistics, engineering, natural sciences, or a related field. Three-year programs are not considered for admission
- A minimum GPA of 3.5 (or the equivalent in other grading scales)
- Personal statement/statement of purpose
- Curriculum Vitae (CV)
- Three Letters of Recommendation
- Transcripts
- Extenuating circumstances statement
- Writing sample
- Description of research
- Diversity statement (strongly encouraged)
- GRE scores are not required, but are recommended particularly for those applying from international institutions for the MS degree
- English language proficiency
Tuition Fees
-
International Applies to you
Applies to youNon-residents33552 USD / year≈ 33552 USD / year - Out-of-State33552 USD / year≈ 33552 USD / year
-
Domestic
Applies to youIn-State21264 USD / year≈ 21264 USD / year
Living costs
Minneapolis
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Financing
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Funding
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Scholarships Information
Below you will find Master's scholarship opportunities for Data Science.
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
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