Duke University

How this program compares

Budget-wise, $67.7K puts this master's program at the 83rd percentile on cost — about 58% above the $42.9K average across 394 comparable listings. It runs on a full-time schedule (on-campus).

Admission Snapshot

Typical admitted student: Applicants must hold a bachelor's degree from an accredited institution with a strong quantitative background; GRE scores are optional to strengthen the application.[1

About This Program

This two-year applied program prepares students to lead data-driven teams by combining rigorous technical training in statistics and computation with professional skills in communication, teamwork, and ethical leadership. Coursework concentrates on Machine Learning and Data Science & Analytics. Most students complete it in about 2 years.

Apply machine learning algorithms to real-world datasets.

At roughly $67.7K total, Duke University's Master in Interdisciplinary Data Science (MIDS) sits above the $42.9K average among AI master's programs we track — the 83rd percentile on price. Applicants should weigh that premium against the program's outcomes and brand.

It is one of 31 AI-related programs we track in North Carolina, of which about 45% offer an online option. On price, it comes in higher than about 55% of the North Carolina programs in our data, where typical tuition runs near $69.0K.

Graduates frequently move into roles such as Data Scientist, with reported salaries around $120,000.

Career Outcomes

Duke University positions this master track for Data Scientist careers — typical offers cluster around $120,000. Its focus on Machine Learning and Data Science & Analytics maps directly to how employers screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 36% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Data Scientist
• 2. Machine Learning Engineer
• 3. Data Analyst
• 4. Business Intelligence Analyst

What You'll Learn

• Apply machine learning algorithms to real-world datasets.
• Design and analyze large-scale data systems.
• Integrate interdisciplinary methods for data-driven decision making.
• Communicate insights through visualization and ethical considerations.

Curriculum Highlights

The curriculum features a technical bootcamp, seven core courses covering data ethics and visualization, a mandatory summer internship, and a year-long capstone project with research faculty or partners.

Top Employers

Top employers include tech giants like Google, Amazon, Microsoft, and consulting firms such as McKinsey and Deloitte.

Admissions

Admission to Duke University's Master in Interdisciplinary Data Science (MIDS) generally expects a bachelor's degree. The GRE is optional here — a growing norm among AI programs — so applicants can often lead with coursework, projects and recommendations instead. Deadlines, testing policies and funding change year to year, so confirm the current requirements on the official program page before applying.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 3
• Resume: Required
• Transcripts: Official transcripts required[1]

Frequently Asked Questions