A gathering of Duke Engineering data science students

Artificial Intelligence for Product Innovation Master of Engineering

Complete on-campus in 12 months and online part-time in 24 months

As a Duke AI for Product Development Master of Engineering student, you'll gain a strong grasp of fundamental skills, as well as the business, policy, and ethical considerations of implementing AI and machine learning in products and services.

Our novel core curriculum was developed with industry input and is structured around the Product Development Process used in industry. 

As a Duke master's student, you will:

  • Build a personal portfolio of real-world, hands-on projects
  • Receive individualized course advising
  • Be engaged with outstanding peers around the world, and with our faculty

The degree can be completed full-time on-campus in 12 months and online part-time in 24 months. Duke undergraduate students can earn the degree in five years through the 4+1:BSE+Master's option »


Curriculum Structure

Mapped to the Product Development Process used in industry

Duke AI in Product Development Master of Engineering graphic of courses mapped to product development process

Browse course descriptions »


Degree Requirements

Pre-Program Preparation

  • Summer Online Python & Data Science Math Boot Camp More »

10 Courses

  • Four (4) Technical Core courses, designed in collaboration with industry leaders
  • Two (2) Elective courses, enabling students to explore more deeply the application of AI in their industry of specialization
  • Two (2) Industry Preparation Core courses, developed with Duke's Law School and Fuqua School of Business
  • Two (2) Professional Development courses, which examine AI operationalization, and the legal, societal and ethical implications of AI

Browse course descriptions »

1 Capstone Project

  • An extended two-semester machine learning/AI project to address a real-world problem or opportunity faced by an industrial company sponsor More »

Industry Seminar Series and Campus Residencies

  • All students participate in a weekly seminar series to learn from industry leaders building AI products
  • Online students also attend two (2) week-long on-campus residencies at Duke

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.

Compare Online and On-Campus

  Online (part-time) On-Campus (full-time)
Minimum Time to Degree 24 months 12 months
Python & Data Science Math Boot Camp
  • Online, spread over 6 weeks
  • Online, 2.5 weeks
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
  • 2 one-week residences at Duke
  • Weekly industry seminar series
  • Weekly industry seminar series
Academic Advising
  • Online interaction with a faculty advisor
  • In-person during residencies
  • In-person and online interaction with a faculty advisor
Career Services & Professional Development Support from career services professionals specialized in assisting engineering master's students

More Details

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Campus—Typical Full-Time Schedule

  Industry Prep Core Technical Core Electives Professional Development
Summer (Prerequisite)  

Online Python & Data Science Math Bootcamp

   
Fall MENG 570:
Business Fundamentals for Engineers

AIPI 510:
 Sourcing Data for Analytics

AIPI 520:
 Modeling Process & Algorithms

AIPI 530:
 Applying AI in Practice

  Industry Seminar Series 1
Spring MENG 540:
 Management of High-Tech Industries

API 540:
Building Products Using Deep Learning

Elective 1

Elective 2

Industry Seminar Series 2

AIPI 549:
Capstone Project 1

Summer      

AIPI 560:
Legal, Societal & Ethical Implications of AI

AIPI 561:
Operationalizing AI

AIPI 550:
Capstone Project 2

Online—Typical Part-Time Schedule

  Industry Prep Core Technical Core Electives Professional Development
Summer (Prerequisite)  

Online Python & Data Science Math Bootcamp

   
Fall 1 MENG 570:
 Business Fundamentals for Engineers

AIPI 510:
Sourcing Data for Analytics

  Industry Seminar Series 1
Spring 1 MENG 540:
 Management of High-Tech Industries

AIPI 520:
 Modeling Process & Algorithms

 

Industry Seminar Series 2

Summer 1  

AIPI 530:
 Applying AI in Practice

 

AIPI 560:
Legal, Societal & Ethical Implications of AI

Residency 1

Fall 2   AIPI 540:
Building Products Using Deep Learning
 Elective 1

 

 

Spring 2      Elective 2 AIPI 549:
Capstone Project 1
Summer 2      

AIPI 550:
Capstone Project 2

AIPI 561:
Operationalizing AI

Residency 2

Residencies for Online Students

To provide an on-campus experience that bonds students to Duke and to each other, the online master's program includes two (2) week-long residencies during program. 

The on-campus residencies provide opportunities to interact with faculty, attend class in person, and to experience Duke-curated professional enrichment activities.

Tuition and Financial Aid

Tuition

For current information about tuition, please visit meng.duke.edu »

Financial Aid

Limited financial aid is available to highly qualified candidates through academic scholarships with an emphasis on increasing diversity within the program. Underrepresented minorities may receive up to 50 percent per year in tuition scholarship through our Diversity Scholarships.  

For more information is available at meng.duke.edu »

Duke Undergrads: 4+1 Option

The Pratt School of Engineering's 4+1:BSE+Master's option allows a Duke student to earn both an undergraduate degree and a master's in just five years. Students may choose to get a headstart on the AI for Product Innovation Master of Engineering during the senior year.

Students who receive admission to the AIPI program through 4+1 may allocate up to four (4) graduate courses taken in the senior year toward Master of Engineering requirements. Participating students may take graduate-level electives, or AIPI core courses, in the senior year. This provides greater flexibility when scheduling the fifth year.

Further details may be found on the Pratt 4+1 webpage. To discuss options for courses to be taken in the senior year toward the AI for Product Innovation MEng, please contact degree program Director Jon Reifschneider at jon.reifschneider@duke.edu.

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