Duke University
Master of Engineering in AI for Product Innovation
How this program compares
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Admission Snapshot
Typical admitted student: A bachelor's degree in engineering, computer science, or a related technical field with a minimum GPA of 3.0 is required, along with relevant coursework in programming, math, or AI fundamentals.
About This Program
This intensive program focuses on the intersection of machine learning and product design, preparing engineers to lead the development of intelligent software solutions in a professional environment.
Career Outcomes
Excel as Machine Learning Engineer in Business AI with machine learning expertise
- 1. AI Product Manager
- 2. Product Innovation Lead
- 3. AI Strategy Consultant
- 4. Machine Learning Product Engineer
What You'll Learn
- Design and manage the full AI product lifecycle from ideation to deployment.
- Apply machine learning and generative AI to solve real-world product challenges.
- Integrate ethical considerations and user needs into AI-driven innovations.
- Lead cross-functional teams in developing scalable AI products.
Curriculum Highlights
The 12-to-16-month curriculum includes technical core courses in AI, product development coursework in collaboration with the business school, and a required industry-connected capstone project.
Top Employers
Top employers include tech leaders like Google, Amazon, Microsoft, and innovative firms such as NVIDIA and startups in AI-driven product development.
Admissions
A bachelor's degree in engineering, computer science, or a related technical field with a minimum GPA of 3.0 is required, along with relevant coursework in programming, math, or AI fundamentals.
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 90+ / IELTS 7.0+)
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