Degree Details

Duke's program is recognized as one of the top applied AI/ML graduate programs in the world

Degree Details

Duke’s program is recognized as one of the top applied AI/ML graduate programs in the world

Overview

Our Master of Engineering in Artificial Intelligence for Product Innovation students develop strong technical skills in AI and machine learning coupled with a deep understanding of how to design and build AI-powered software products.

Graduates go on to work in leading companies solving challenging problems across many industries—including tech, healthcare, energy, retail, transportation, and finance. Some of our students go on to found their own entrepreneurial ventures.

At Duke, you’ll learn to:

  • Design and develop machine learning systems for scale, security and usability
  • Apply traditional machine learning and deep learning models to solve challenging problems across domains
  • Build full-stack software applications integrating machine learning models utilizing the latest methods and technologies
  • Design and deploy software applications in production

This program may be for you if you have an educational or work background in engineering, science or technology and aspire to a career working hands-on in AI. See our application requirements for details.

Industry-Connected Curriculum

This degree’s core curriculum was developed in collaboration with the industry.

  • Build a personal portfolio of real-world, hands-on AI and machine-learning projects
  • Receive individual advising, academic and career, from outstanding, world-class faculty
  • Be engaged with peers from around the world as part of a small, intimate, and immersive cohort

We prepare graduates who are ready to solve problems on the job, starting on Day 1.  

Our curriculum covers the theory and application of AI and machine learning, heavily emphasizing hands-on learning via real-world problems and projects in each course.  

Students also have two opportunities to work directly with industry leaders during the program: through the semester-long industry project and their summer internship.

Flexibility and Options

12 or 16 month on-campus or 24 months online

Innovative and immersive, you can complete this Duke master’s degree in 12 or 16 months on-campus, or online part-time in just 24 months.

12-Month Accelerated Option

Significantly more affordable than a traditional master’s program—in this option, pay tuition for only two (2) full semesters plus three (3) summer session credits.

16-Month Standard Track

Pursue this degree over three (3) full semesters plus the summer session—allowing you time to take additional electives and specialize. Students pursuing this path may take a partial or whole load of courses during their final semester.

4+1: BSE + Master’s Option for Duke Undergraduates

Duke undergraduate students can complete undergrad and this master’s degree in just five (5) years.

Scholarship opportunity: The AI 4+1 BSE+Master’s scholarship covers 20 percent of the costs. Eligibility and other conditions apply.

MD + MEng in Artificial Intelligence Dual Degree

Medical students at Duke can complete this degree during their third year. See School of Medicine bulletin for details.

Scholarship opportunity: The MD+MEng AI scholarship covers 20 percent of the costs. Eligibility and other conditions apply.

Curriculum Schedules

The core of the curriculum follows a cohort-based course sequence. Select an option to view the schedule options.

  • Summer Fall Spring Summer
    Pre-requisite
    AIPI 503: Python & Data Science Math Bootcamp
    AIPI 510: Sourcing Data for Analytics MENG 540: Management of High-tech Industries AIPI 560: Legal, Societal & Ethical Implications of AI
    AIPI 520: Modeling Process & Algorithms AIPI 540: Deep Learning Applications AIPI 561: Operationalizing AI (MLOps)
    AIPI Departmental Elective AIPI 549: Industry Capstone Project Industry Internship or Project
    MENG 570: Business Fundamentals for Engineers Technical Elective 1
    AIPI 501: Industry Seminar Series Technical Elective 2
    EGR 590: Career Strategy & Design
  • Summer Fall 1 Spring Summer Fall 2
    Pre-requisite—
    AIPI 503: Python & Data Science Math Bootcamp
    AIPI 510: Sourcing Data for Analytics AIPI 540: Deep Learning Applications AIPI 560: Legal, Societal & Ethical Implications of AI AIPI Departmental Elective
    AIPI 520: Modeling Process & Algorithms AIPI 549: Industry Capstone Project AIPI 561: Operationalizing AI (MLOps) Technical Elective 2
    MENG 570: Business Fundamentals for Engineers MENG 540: Management of High-Tech Industries Industry Internship or Project
    AIPI 501: Industry Seminar Series Technical Elective 1
    EGR 590: Career Strategy & Design
  • Pre-Program Year 1
    Summer  Fall
    Spring
    Summer
    Pre-requisite
    AIPI 503:
    Python & Data Science Math Bootcamp
    AIPI 510:
    Sourcing Data for Analytics
    AIPI 520:
    Modeling Process & Algorithms
    AIPI 540:
    Deep Learning Applications
    MENG 570:
    Business
    Fundamentals for Engineers
    MENG 540:
    Management of
    High-Tech Industries
    AIPI 501:
    Industry Seminar Series
    On-Campus
    Residency
    Year 2
    Fall
    Spring
    Summer
    AIPI
    Departmental Elective
    AIPI 549:
    Industry Capstone Project
    AIPI 560: Legal,
    Societal & Ethical Implications of AI
    Technical
    Elective 1
    Technical
    Elective 3
    AIPI 561: Operationalizing
    AI (MLOps)
    On-Campus Residency

     

Degree Requirements

Pre-Program Bootcamp

  • Summer Online Python & Data Science Math Boot Camp

10 Courses

  • Four (4) Technical AI/ML courses—a strong technical foundation
  • Three (3) Product Development courses—developed with Duke’s Law School and Fuqua School of Business including the business, legal & ethical aspects of AI products
  • Three (3) Technical electives—specialize in preparation for your chosen career

Browse course descriptions

2 Industry Experiences

  • Industry project—design a solution to an authentic opportunity offered by a sponsoring organization
  • A summer internship or industry project—gain industry experience

Additional Requirements

  • Learn from leaders building AI products during regular industry seminars
  • Jump-start your professional development with our Career Strategy and Design workshop for on-campus students
  • Meet peers and faculty during two (2) required residencies on the Duke campus for online students

Compare Online and On-Campus

The choice of online or on-campus is up to you – all students take the same courses, learn from the same faculty, and earn the same Duke degree.

 ItemOnline (part-time)On-Campus (full-time)
Time to Degree
  • 24 months
  • 12 months or 16 months
Python & Data Science Math Boot Camp
  • Online 4-week part-time
  • Online 4-week part-time
Class Experience
  • Live and recorded classes
  • Online interaction with faculty and peers
  • Class attendance at Duke
  • In-person and online interaction with faculty and peers
Professional Development
  • Two spring residences on-campus at Duke
  • Industry seminar series
  • Industry seminar series
Academic Advising
  • Online interaction with a faculty advisor
  • In-person interaction during on-campus residencies
  • In-person and online interaction with a faculty advisor
Career Services & Professional Development