Carnegie Mellon University

How this program compares

Carnegie Mellon University's MS in Machine Learning lists about $120.8K total tuition — about 182% above the $42.9K AI master's average (97th percentile in our data). It runs on a full-time schedule (on-campus).

Admission Snapshot

Typical admitted student: Applicants must hold a bachelor's degree with a strong background in computer science, including programming skills, and mathematics such as probability, statistics, matrix algebra, and multivariate calculus. GRE scores are optional, with TOEFL/IELTS required for international students.

About This Program

Carnegie Mellon's MS in Machine Learning is offered by the world's first dedicated Machine Learning Department, and it remains the benchmark against which other ML master's programs are measured. The curriculum is rigorous and theory-forward, covering statistical foundations, optimization, deep learning, and large-scale ML systems.

CMU's depth across the entire AI stack — robotics, language technologies, computer vision, and systems — means ML students collaborate across an exceptional research ecosystem. Graduates are heavily recruited into research scientist and applied ML roles at the most competitive labs and companies.

Career Outcomes

Graduates of Carnegie Mellon University's MS in Machine Learning most often target Machine Learning Engineer roles, where reported compensation runs around $140,000. Its focus on Machine Learning and AI Engineering / Applied AI maps directly to how employers screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 36% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Machine Learning Engineer
• 2. AI Research Scientist
• 3. Data Scientist
• 4. Applied ML Specialist

What You'll Learn

• Develop and analyze machine learning algorithms for predictive modeling
• Apply deep learning techniques to image and language data
• Design probabilistic models for uncertainty quantification
• Implement reinforcement learning systems for decision-making
• Evaluate and optimize ML models for real-world deployment

Curriculum Highlights

The curriculum requires core courses in machine learning and statistics, specialized electives, and a summer research or industry practicum.

Top Employers

Top employers include Google, Meta, Amazon, Microsoft, and research institutions like OpenAI.

Admissions

Admission to Carnegie Mellon University's MS in Machine Learning generally expects a bachelor's degree. The GRE is optional here — a growing norm among AI programs — so applicants can often lead with coursework, projects and recommendations instead. Deadlines, testing policies and funding change year to year, so confirm the current requirements on the official program page before applying.

Application Materials

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

Frequently Asked Questions