Overview
The Data Analytics Engineering M.Sc. at George Mason University provides students with a deep understanding of the technologies and methodologies essential for modern data-driven decision-making. This interdisciplinary programme bridges the gap between complex data structures and actionable business intelligence. Students develop the technical proficiency required to manage, analyse, and interpret vast datasets across various information-intensive industries.
Why Data Analytics Engineering at George Mason University?
George Mason University offers a unique strength in this field by leveraging an extensive history in information technology, global studies, and sociological research. The Volgenau School of Engineering provides an environment where students learn to build structures that contain and organise gigantic fields of data. This interdisciplinary approach combines computer science, statistical science, and systems analytics to prepare graduates for a rapidly growing employment market. The programme is designed to help students predict consumer behaviours, social trends, and global challenges such as climate change or disease threats.
Tuition Fee Breakdown
- International fee: USD 41124 per year
- National fee: USD 41124 per year
- Local fee: USD 18060 per year
Visit the Fees and Funding section for a breakdown in your local currency.
Syllabus
The curriculum covers a broad range of technical subjects designed to foster expertise in analytics and engineering. Modules may include:
- Data Mining
- Information Technology
- Statistical Models
- Predictive Analytics
- Optimization
- Risk Analysis
- Data Visualization
- Digital Forensics
- Financial Engineering
Careers with Data Analytics Engineering
Graduates are prepared for high-level roles as data scientists, analysts, and engineers within diverse sectors. The programme is particularly suited for those aiming to work in finance, marketing, operations, and business intelligence. Because the curriculum focuses on the deployment of interdisciplinary systems analytics, alumni are well-equipped to work in specialised fields such as geoscience, bioscience, and operations research. The employment outlook for these specialised engineers continues to grow as organisations increasingly rely on large-scale data consumption to drive their strategic goals.
Programme Structure
Courses include:
- Analytics: Big Data to Information
- Principles of Data Management and Mining
- Theory and Applications of Data Mining
- Analytics and Decision Analysis
- Operations Research: Deterministic Models
- Applied Statistics
Key information
Duration
- Full-time
- 24 months
Start dates & application deadlines
- Starting
- Apply before
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- Starting
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Language
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Credits
Delivered
Campus Location
- Fairfax, United States
Disciplines
General Engineering & Technology Data Analytics View 398 other Masters in Data Analytics in United StatesWhat students do after studying
Academic requirements
English requirements
Prepare for Your English Test
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- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- College Transcripts
- 2 Letters of Recommendation
- Goals Statement
- Resumé
Tuition Fees
-
International Applies to you
Applies to youNon-residents41124 USD / year≈ 41124 USD / year - Out-of-State41124 USD / year≈ 41124 USD / year
-
Domestic
Applies to youIn-State18060 USD / year≈ 18060 USD / year
Living costs
Fairfax
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 Analytics Engineering.
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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