Carnegie Mellon University
MS in AI Engineering (ETIM Track)
How this program compares
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Admission Snapshot
Typical admitted student: Requires a bachelor's degree in engineering, computer science, or a related technical field with a minimum GPA of 3.0, strong quantitative background including calculus and linear algebra, and programming experience; GRE is optional but recommended for competitive applicants.
About This Program
This interdisciplinary degree combines artificial intelligence fundamentals with innovation management to prepare STEM professionals for technology leadership roles.
Career Outcomes
Lead as Product Analyst in Business AI with innovation management expertise
- 1. AI Engineer
- 2. Machine Learning Engineer
- 3. AI Systems Architect
- 4. Technology Innovation Manager
What You'll Learn
- Design and deploy scalable AI models for real-world engineering applications
- Optimize machine learning systems for performance and efficiency
- Integrate AI technologies into engineering workflows and products
- Apply engineering principles to AI ethics, reliability, and innovation management
Curriculum Highlights
The structure includes core engineering innovation courses, artificial intelligence fundamentals, a capstone project, and a professional internship.
Top Employers
Top employers include Google, Meta, Amazon, NVIDIA, and tech consultancies like McKinsey Digital.
Admissions
Requires a bachelor's degree in engineering, computer science, or a related technical field with a minimum GPA of 3.0, strong quantitative background including calculus and linear algebra, and programming experience; GRE is optional but recommended for competitive applicants.
Application Materials
- Statement of Purpose: Required
- Letters of Recommendation: 3
- Resume: Required
- Transcripts: Official transcripts required
Academic Requirements
- Degree Required: Bachelor's degree
- GRE/GMAT: Optional
- TOEFL/IELTS: Required for international students (TOEFL 100+ / IELTS 7.0+)
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