MasterOn-CampusFull-Time

University of Michigan‑Ann Arbor

MEng in Data Science and Machine Learning

Ann Arbor, Michigan1 years$35K total tuition
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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 $34.8K in total tuition, the MEng in Data Science and Machine Learning sits roughly 18% below the $42.4K average for AI master's programs in our database — placing it in the 54th percentile on cost among the 531 we track at this level.

Est. Salary$120,000 Machine Learning Engineer
Job Growth+36%
Top RoleData Scientist
FormatOn-Campus

Admission Snapshot

Degree Required
Bachelor's degree
Duration
1 year
Est. Tuition
$35K total
Format
On-Campus
Schedule
Full-Time
GRE / GMAT
Required
Concentrations
Machine Learning, Computer Vision

Typical admitted student: A bachelor's degree in computer science, mathematics, engineering, or a related quantitative field with a minimum GPA of 3.0 is required, along with programming experience and coursework in linear algebra, calculus, and statistics.

About This Program

Michigan's MEng in Data Science and Machine Learning (Ann Arbor) is an engineering-focused professional master's from one of the country's premier public universities. It emphasizes applied ML systems, data engineering, and production-oriented skills.

The program draws on Michigan's deep engineering resources and a strong national alumni network, suiting engineers who want a rigorous, build-focused data science credential.

Why students choose it: Engineering-focused, production-oriented ML from a premier public university.

Career Outcomes

Excel as Data Scientist in Cross-Industry AI with machine learning expertise

  • 1. Data Scientist
  • 2. Machine Learning Engineer
  • 3. AI Research Scientist
  • 4. Data Analytics Manager

What You'll Learn

  • Design and implement machine learning models for predictive analytics
  • Analyze large-scale datasets using advanced statistical techniques
  • Apply deep learning to computer vision and natural language tasks
  • Develop scalable data pipelines for real-world applications

Curriculum Highlights

The highly structured program requires 26 credits, emphasizing hands-on projects and design. The curriculum includes core courses in estimation, filtering, and detection alongside technical electives and leadership training.

Top Employers

Top employers include Google, Amazon, Microsoft, Meta, and consulting firms like McKinsey and Deloitte.

Admissions

A bachelor's degree in computer science, mathematics, engineering, or a related quantitative field with a minimum GPA of 3.0 is required, along with programming experience and coursework in linear algebra, calculus, and statistics.

Application Materials

  • Statement of Purpose: Required
  • Letters of Recommendation: 2–3
  • Resume: Required
  • Transcripts: Official transcripts required

Academic Requirements

  • Degree Required: Bachelor's degree
  • GRE/GMAT: Optional
  • TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)

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