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Master of Engineering in Artificial Intelligence for Product Innovation

Program Code: E-EGR-AIPI
Degree Designation: Master of Engineering
Department: Institute for Enterprise Engineering
Website: ai.meng.duke.edu/degree

Program Summary

Students in the MEng Artificial Intelligence for Product Innovation On-Campus Program develop strong technical skills in Artificial Intelligence together with an understanding of software product design and development. After graduation, students are well-equipped to build AI-based products and systems within large companies or through their own entrepreneurial ventures. Graduates go on to work in leading companies solving difficult problems across many industries, such as tech, healthcare, energy, retail, transportation and finance. 

Through the program, students will learn to: 

  • Identify and assess opportunities for the application of AI/ML in products 

  • Design data pipelines and ML systems for scale, security and usability 

  • Apply traditional ML 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 

Innovative and immersive, this on-campus master's degree can be completed in 12 or 16 months.

View Master of Engineering overview and academic policies.

Admissions Policies & Practices

The Duke Artificial Intelligence for Product Innovation Master of Engineering (MEng) is designed to be accessible to participants from a variety of engineering and science backgrounds. 

Applicants should have: 

  • An undergraduate degree in science or engineering (or equivalent technical work experience if your degree is in a non-technical field)

  • Proficiency in one or more programming languages (Python preferred)

  • Sufficient DUOLINGO, IELTS, or TOEFL English Language Testing scores (official results required; international students only)

  • Two (2) semesters of calculus

Prior coursework in probability and statistics and linear algebra is highly encouraged, but not required for admission. 

4+1 Program for Duke Students 

Advanced Duke undergraduates may participate in a 4+1 Program where both a bachelor’s degree and a MEM/MEng degree may be completed in about five years. 4+1 Program participants matriculating to the Artificial Intelligence MEng program may typically apply up to two graduate courses (at the 500 level or above) that were taken during their undergraduate career but not used to fulfill undergraduate degree requirements toward master's degree requirements. 

Additional academic policies for Duke undergraduates in the 4+1 Program can be found at prattprofessional.bulletins.duke.edu/policies/academic/early-programs.

MD/MEng in Engineering Program (School of Medicine) 

This five-year program is designed for MD candidates who wish to also obtain a Master of Engineering (MEng) degree. In brief, students spend four years (Years 1, 2, 4 and 5) in medical school to fulfill the MD curriculum requirements, and one year (Year 3) to take the required MEng courses detailed below. In the fourth year, students work on development of new technologies or engineering approaches (including optimization/system analysis or feasibility analysis, etc.) for improving healthcare, improving public health, or reducing health hazards and write a thesis, for which they will receive School of Medicine credit in fulfillment of their Third Year thesis requirement. 

Additional academic policies for the MD/MEng in Engineering program can be found at medicine.bulletins.duke.edu/som-programs/dr/md#dual-degree-programs1.

Class Attendance Policy for On-Campus AI MEng Students 

On-campus AI MEng students are expected to attend class regularly and in person, adhering to the Graduate dates within Duke’s Academic Calendar when applicable.

It is critical that students attend the first day and the last day of class for all courses in which they are enrolled, as well as all applicable Orientation programming for new students in August.

At the conclusion of the first class of each course, faculty will report any unexcused absences to the AI MEng program administration. Those students may then be dropped from the course at the program director’s discretion.

Note that instructors may have additional attendance guidelines for their class that you must follow that go beyond the baseline of this attendance policy. Please refer to each course’s syllabus for more specific information regarding individual professors’ attendance policies.

A student seeking an “excused” absence must work directly with her or his course faculty (or the program director and master’s coordinator in the case of Orientation programming). Students must initiate the request in advance and as soon as possible.

A student may be excused from attendance due to truly extenuating circumstances such as significant illness, personal/family emergency, or important religious observance.

Whether an absence is excused or not, a student will be held fully accountable for any in-class graded participation or assignments an absence caused the student to miss.

Academic Requirements

  • Bootcamp and Career Strategy (complete all):

    • AIPI 503  (Python Bootcamp)

    • EGR 590-1 (topic: CAREER DESGN & STRAT AIPI)

  • Technical Core (complete all):

    • AIPI 501 (AIPI Seminar)

    • AIPI 510 (Sourcing Data for Analytics)

    • AIPI 520 (Modeling Process and Algorithms)

    • AIPI 540 (Deep Learning Applications)

    • AIPI 561 (Operationalizing AI)

  • Product Development Core (complete all):

    • MENG 540 (Management of High Tech Industries)

    • MENG 570 (Business Fundamentals for Engineers)

    • AIPI 560 (Legal, Societal, and Ethical Implications of AI)

  • Industry Project (complete all):

    • AIPI 549 (Capstone Practicum 1)

  • Internship/Project and Assessment (complete all):

    • MENG 550 (Master of Engineering Internship/Project)

    • MENG 551 (Master of Engineering Internship/Project Assessment)

  • AI Departmental Electives (complete 3 credits from the following):

    • IDS 721 or AIPI 500-599

  • Technical Electives (complete 6 credits from the following):

    • IDS 721

    • AIPI 510-590L

    • BME 500-850

    • CEE 500-890

    • CYBERSEC 510-590L

    • DESIGNTK 500-590L

    • ECE 500-781

    • EGRMGMT 510-590L

    • FINTECH 510-590L

    • GAMEDSGN 500-590L

    • ME 500-775

    • Other pre-approved courses may also count