Artificial Intelligence for Product Innovation Master of Engineering
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.
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.
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.
Career paths
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 health care 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).
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 |
Degree Requirements
Entry Bootcamp
- Summer Online Python & Data Science Math Boot Camp More »
10 Courses
- Four (4) AI/ML courses—a strong technical foundation
- Two (2) Operations courses—deploying and managing AI products in production (MLOps), and the legal, societal and ethical implications of AI
- Two (2) Management courses—developed with Duke's Law School and Fuqua School of Business
- Two (2) Electives—specialize in preparation for your chosen career
2 Industry Experiences
- Capstone project—design a solution to an authentic opportunity offered by a sponsoring organization
- Summer internship or industry project—gain industry experience
Industry Seminar Series and Campus Residencies
- Learn from leaders building AI products during regular industry seminars
- Meet peers and faculty during two (2) required week-long residencies on the Duke 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.
Compare Online and On-Campus
| Item | Online (part-time) | On-Campus (full-time) |
|---|---|---|
| Time to Degree | 24 months | 12 or 16 months |
| Python & Data Science Math Boot Camp | Online 6-week part-time | Online 6-week part-time |
| Class Experience |
|
|
| Professional Development |
|
Industry seminar series |
| Academic Advising |
|
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 | Support from career services professionals specialized in assisting engineering master's students |
More Program Details
Tuition and Financial Aid
Tuition
Campus Master of Engineering Programs
Tuition
In General
Tuition for campus-based Duke Master of Engineering programs for the 2022-2023 academic year is $30,250 per semester taken at the university.
Tuition for the Master of Engineering in Artificial Intelligence for Product Innovation over two semesters and a summer session would result in a total tuition cost of $69,575. The internship course does not incur tuition charges.
2022-2023 Campus Tuition, Fees, and Estimated Expenses
For 1 year of study
| Item | Amount |
|---|---|
| Tuition | $69,575 ($30,250/semester and $9,075/summer session)* |
| Health Fee | $1,125* |
| Health Insurance | $3,785** |
| Graduate Student Activity Fee | $37 |
| Graduate Student Services Fee | $22* |
| Transcript Fee | $120* |
| Recreation Fee |
$342 |
| Room | $13,920 |
| Board | $4,740 |
| Books | $835 |
| Transportation and Misc. | $7,512 |
|
TOTAL |
$102,013 |
| Notes
* Tuition, fees, and estimates subject to confirmation each May ** Required unless you can show proof of comparable private insurance coverage Also:
|
|
Normal Program Duration
- The normal duration of the Master of Engineering in Artificial Intelligence for Product Innovation program is one year of study (2 semesters and a summer session), however, the program can be extended for an additional Fall semester to complete in 16 months
- The normal load is 4 courses (12 units) per semester in the first year
Online Master of Engineering Programs
Tuition for online Duke Master of Engineering programs for the 2022-2023 academic year is $9,075 per course taken at the university.
In general, completion of the 30 required credits over five semesters would result in a total tuition cost of $90,750. Please note that the internship courses do not incur tuition charges.
2022-2023 Online Tuition, Fees, and Estimated Expenses
| Item |
Amount |
|---|---|
| Tuition |
$90,750 ($18,150 per semester) * |
| Transcript Fee | $120 * |
| Residency Fee |
$2,540 ($1,270/residency) |
| Books | $668 * |
| TOTAL | $94,078 |
| Notes
* Students typically take 2 courses per semester. Tuition, fees, and estimates subject to confirmation each May Also:
|
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Transcript Fee
All entering students will be charged in the first semester a one-time mandatory fee of $120 for transcripts. This fee entitles the student to an unlimited number of Duke transcripts.
Transportation and Parking
Online Master of Engineering students will be responsible for arranging their own travel to Duke, but transportation and parking will be provided once on campus.
Payment of Accounts
The Office of the Bursar will issue invoices to registered students for tuition, fees, and other charges approximately four to six weeks prior to the beginning of classes each semester. The total amount due on the invoice is payable by the invoice late payment date, which is normally one week prior to the beginning of classes. A student is required to pay all invoices as presented and will be in default if the total amount is not paid in full by the due date. A student in default will not be allowed to receive a transcript of academic records or receive a diploma at graduation.
Contact Duke's Office of the Bursar for:
- Monthly Payment Option
- Late Payment Charge
- Refunds for Withdrawal from School during fall and spring semesters
Online Certificate Programs
Tuition
Tuition for the Graduate Certificate in AI Foundations for Product Innovation in the 2022-2023 academic year is $7,659 per course.
There are two semesters per academic year. Students typically take one course per semester. At current rates, completion of the four required courses to earn a stand-alone online certificate would result in a total tuition cost of $30,636.
Transcript Fee
All entering students will be charged in the first semester a one-time mandatory fee of $120 for transcripts. This fee entitles the student to an unlimited number of Duke transcripts.
Not Eligible for VA Benefits or Federal Student Aid
These stand-alone online certificate programs are not currently eligible for VA benefits or federal student aid.
Important Note for International Applicants
Please Note: This stand-alone online certificate program does NOT qualify students for U.S. visa sponsorship.
Gainful Employment Disclosures*
Program Length
- Typically 2 years for Business Foundations for Engineers Certificate, assuming 1 course per semester
- Typically 15 months for AI Foundations for Product Innovation Certificate (1 course per semester, including summer)
Program Costs
The amounts shown below include costs for the entire program, assuming normal time to completion. There may be additional costs for living expenses. Note that this information is subject to change:
| Item | Amount |
|---|---|
| Tuition | $7,659 per 3-credit class, and a total of $30,636 for the certificate ** |
| Transcript Fee | $120 ** |
| Books | $334 |
| TOTAL | $31,090 |
|
Notes ** Duke may change its tuition for each academic year and this estimate is based on current academic year tuition charges |
|
Student Loans
- Information about average student debt, monthly debt expense and debt interest rate have been withheld since fewer than 10 students have completed this program
Job Placement Rates
- We are not currently required to calculate a job placement rate for program completers
- Program graduates are employed in the following fields:
- Information Technology
- Manufacturing
- Science, Technology, Engineering, and Mathematics
- Transportation, Distribution, and Logistics
- The program does not meet any licensing requirements
- Additional Information—Date Created: 3/15/2021
* These disclosures are required by the U.S. Department of Education
For current information about tuition, please visit meng.duke.edu »
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 scholarship through our Diversity Scholarships. All applicants to the AIPI program are considered for available financial assistance at the time of program application.
More information is available at meng.duke.edu »
Duke Undergrads: 4+1: BSE+Master's
The Pratt School of Engineering's 4+1: BSE+Master option allows Duke students to earn both an undergraduate degree and a master's in just five years. Students may choose to start the AI for Product Innovation Master of Engineering during their undergraduate 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, and Duke 4+1 students are eligible for the AIPI Duke 4+1 scholarship.
Further details may be found on the 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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