Duke University - Pratt School of Engineering
Master of Engineering in AI for Product Innovation
Durham, USA
Master degree
DURATION
24 months
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
EARLIEST START DATE
TUITION FEES
USD 30,250 / per semester
STUDY FORMAT
Distance Learning, On-Campus
* on-campus/online round 1: January 15 | on-campus round 2: March 15 | online round 2: April 15
Key Summary
Our program is recognized as one of the top applied AI/ML graduate programs in the world.
Students in our MEng AI for Product Innovation program develop strong technical skills in AI and machine learning together with an understanding of how to design and build AI-powered software products.
Graduates go on to work in leading companies solving difficult problems across many industries, such as tech, health care, energy, retail, transportation, and finance—or pursue their own entrepreneurial ventures.
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;
- Our students come from a variety of engineering and science backgrounds.
Flexibility and Options
12 or 16 months on-campus, or 24 months online
Innovative and immersive, this master's degree can be completed 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 Option
Pursue this degree over three (3) full semesters plus summer—allowing you time to take additional electives and specialize. Students pursuing this path may take a partial load or a full load of courses during their final semester.
4+1: BSE+Master's Option for Duke Undergrad
Duke undergraduate students can complete undergrad and this master's degree in just five (5) years.
Scholarship opportunity: The AIPI 4+1 scholarship covers 20 percent of the costs. Eligibility and other conditions apply.
MD-Master of Engineering in AI for Product Innovation Dual Degree
Medical students at Duke can complete this degree during the Third Year.
Scholarship opportunity: The MD-MEng AIPI scholarship covers 20 percent of the costs. Eligibility and other conditions apply. Offered in partnership with Duke MEDx.
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.
Financial Aid
Limited merit-based financial aid is available to highly qualified candidates through academic scholarships with an emphasis on increasing diversity within the program. U.S. Citizens or Permanent Residents who are underrepresented minorities may receive up to 50 percent per year in tuition scholarships through our Diversity Scholarships. All applicants to the AIPI program are considered for available financial assistance at the time of program application.
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 & immersive cohort.
We prepare graduates who are ready to solve problems on the job, starting on Day 1.
Our curriculum covers both the theory and application of AI and machine learning, with a heavy emphasis on 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 capstone project and through their summer internship.
Curriculum Schedules
The core of the curriculum follows a cohort-based course sequence.
On-Campus Accelerated Option: 12 Months
| Summer | Fall | Spring | Summer |
|---|---|---|---|
| Pre-requisite— | 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 530: Optimization in Practice OR AIPI 531: Deep Reinforcement Learning Applications | AIPI 549: Industry Capstone Project | Industry Internship or Project | |
| MENG 570: Business Fundamentals for Engineers | Elective 1 | ||
| AIPI 501: Industry Seminar Series | Elective 2 |
On-Campus: 16 Months
| Summer | Fall 1 | Spring | Summer | Fall 2 |
|---|---|---|---|---|
| Pre-requisite— | AIPI 510: Sourcing Data for Analytics | AIPI 540: Deep Learning Applications | AIPI 560: Legal, Societal & Ethical Implications of AI | AIPI 530: Optimization in Practice OR AIPI 531: Deep Reinforcement Learning Applications |
| AIPI 520: Modeling Process & Algorithms | AIPI 549: Industry Capstone Project | AIPI 561: Operationalizing AI (MLOps) | Elective 2 | |
| MENG 570: Business Fundamentals for Engineers | MENG 540: Management of High-Tech Industries | Industry Internship or Project | ||
| AIPI 501: Industry Seminar Series | Elective 1 |
Part-time Online: 24 Months
| Semester | Course 1 | Course 2 | Additional Requirements |
|---|---|---|---|
| Summer 1 | Pre-requisite— AIPI 503: Python & Data Science Math Bootcamp | ||
| Fall 1 | AIPI 510: Sourcing Data for Analytics | MENG 570: Business Fundamentals for Engineers | AIPI 501: Industry Seminar Series |
| Spring 1 | AIPI 520: Modeling Process & Algorithms | MENG 540: Management of High-Tech Industries | |
| Summer 2 | AIPI 540: Deep Learning Applications | On-campus Residency | |
| Fall 2 | AIPI 530: Optimization in Practice or AIPI 531: Deep Reinforcement Learning Applications | Elective 1 | |
| Spring 2 | AIPI 549: Capstone Project | Elective 2 | |
| Summer 3 | AIPI 560: Legal, Societal & Ethical Implications of AI | AIPI 561: Operationalizing AI (MLOps) | On-campus Residency
|
Graduates from our program go on to work in a variety of industries depending on their interests and backgrounds.
Some join the largest technology, engineering, and healthcare companies while others have started their own startup ventures. Many students choose to pursue one of two different roles within companies across industries: ML Engineer, and Data Scientist.
To best prepare students for these career trajectories, the AIPI program offers two different optional tracks, differentiated primarily through the choice of electives. In addition, students may elect to develop their own track by taking electives across the Pratt School of Engineering and elsewhere within Duke.
Machine Learning Engineering Track
Prepare for a career in designing, building, and deploying ML models and software applications
- Sharpen your software development skills and build expertise in AI and machine learning;
- Build a strong foundation in the theory and programming of ML, together with MLOps skills;
- Learn to design, build and deploy machine learning models in production;
- Take elective courses in data engineering, cloud computing, computer vision, NLP, or reinforcement learning.
Students who have prior background in programming or software development and an interest in a career path as an ML Engineer are encouraged to pursue this track.
Data Science Track
Prepare for a career in analyzing and modeling data to solve domain-specific problems
- Leverage your educational or work background in a field of engineering, medicine, or science together with new skills in data analysis and machine learning;
- Solve challenging problems in your field;
- Take elective courses in statistical analysis, data visualization, optimization, or modeling.
Students who have a background in a field of engineering, medicine, or science not related to computer science, and desire to merge their domain expertise with ML skills to pursue a career path as a Data Scientist are encouraged to pursue this track.
Design Your Own Track
Customize your own pathway through the strategic choice of electives from the Pratt School of Engineering or elsewhere in Duke (with approval).