Duke University

How this program compares

Budget-wise, $117.9K puts this master's program at the 97th percentile on cost — about 175% above the $42.9K average across 394 comparable listings. It runs on a full-time schedule (on-campus).

Admission Snapshot

Typical admitted student: A bachelor's degree in electrical engineering, computer engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with coursework in linear algebra, probability, and programming.

About This Program

This Master of Science program offers rigorous technical depth in computer engineering, focusing on the mathematical foundations of machine learning and the design of AI-driven systems. Coursework concentrates on MLOps/AI Engineering and Machine Learning. Most students complete it in about 1.5 years.

Implement and optimize machine learning models for data analytics in engineering systems.

Estimated total tuition is $117.9K, above the $42.9K average for AI master's programs in our database and in the 97th percentile on cost at this level. 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 84% of the North Carolina programs in our data, where typical tuition runs near $69.0K.

Graduates frequently move into roles such as Machine Learning Engineer, with reported salaries around $130,000.

Career Outcomes

Graduates of Duke University's MS in ECE - Data Analytics & Machine Learning most often target Machine Learning Engineer roles, where reported compensation runs around $130,000. Its focus on MLOps/AI Engineering and Machine Learning maps directly to how employers screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 23% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Machine Learning Engineer
• 2. Data Scientist
• 3. AI Systems Engineer
• 4. Computer Vision Specialist

What You'll Learn

• Implement and optimize machine learning models for data analytics in engineering systems.
• Apply deep learning techniques to signal processing and image analysis.
• Analyze large datasets using advanced statistical methods and algorithms.
• Design AI-driven solutions for real-world ECE applications like networking and embedded systems.

Curriculum Highlights

The track-based structure allows for deep specialization in machine learning and AI, complemented by research seminars and the option to complete a faculty-supervised thesis.

Top Employers

Top employers include tech giants like Google, Microsoft, NVIDIA, and engineering firms such as Intel and Qualcomm.

Admissions

Admission to Duke University's MS in ECE - Data Analytics & 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: 3
• Resume: Required
• Transcripts: Official transcripts required

Frequently Asked Questions