Duke University

How this program compares

Duke University's Master of Engineering Management - Data Analytics and Machine Learning lists about $69.6K total tuition — about 62% above the $42.9K AI master's average (85th percentile in our data). It is one of the 54% of programs in our database offered fully or partly online.

Admission Snapshot

Typical admitted student: A bachelor's degree in engineering, computer science, or a related quantitative field with a minimum GPA of 3.0 is required, along with relevant professional experience preferred for this management-focused master's program.

About This Program

This program combines a core management curriculum with technical electives in data science, designed for engineers and scientists who want to lead technology-focused organizations. Coursework concentrates on Cybersecurity Management, Risk & Governance and AI Engineering / Applied AI. Most students complete it in about 1.5 years.

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 61% of the North Carolina programs in our data, where typical tuition runs near $69.0K.

Graduates frequently move into roles such as Product Analyst, with reported salaries around $135,000.

Integrate machine learning models with engineering management principles for data-driven decisions.

At roughly $69.6K total, Duke University's Master of Engineering Management - Data Analytics and Machine Learning sits above the $42.9K average among AI master's programs we track — the 85th percentile on price. Applicants should weigh that premium against the program's outcomes and brand.

Career Outcomes

Duke University positions this master track for Product Analyst careers — typical offers cluster around $135,000. Its focus on Cybersecurity Management, Risk & Governance and AI Engineering / Applied AI maps directly to how employers in business ai screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 15% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Data Analytics Manager
• 2. Machine Learning Operations Lead
• 3. Engineering Program Manager
• 4. Business Intelligence Director

What You'll Learn

• Integrate machine learning models with engineering management principles for data-driven decisions.
• Apply data analytics techniques to optimize business operations and financial strategies.
• Develop leadership skills for managing AI and analytics projects in technical environments.
• Analyze complex datasets using visualization and predictive modeling tools.

Curriculum Highlights

The structure includes core courses in finance and marketing, a specialized track in data analytics, a seminar series with industry experts, and a required internship for professional experience.

Top Employers

Top employers include tech firms like Google, Amazon, and Microsoft, as well as engineering consultancies and high-tech industries such as aerospace and manufacturing.

Admissions

Admission to Duke University's Master of Engineering Management - Data Analytics and Machine Learning 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: 2–3
• Resume: Required
• Transcripts: Official transcripts required

Frequently Asked Questions