NC

Master's in DS/DA
On-Campus

Duke University

Master in Interdisciplinary Data Science (MIDS)

  • Durham
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.

Student Reviews
Write a Review
What You'll Learn

Graduates gain expertise in statistical modeling, machine learning, data wrangling, and database systems, while learning to ask critical questions and provide actionable insights using real-world datasets.

For detailed, official program information including specific curriculum, faculty, research opportunities, and application requirements:
Visit Official Program Website
Typical Curriculum Structure
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.
Typical Course Topics
1. Data Structures and Algorithms 2. Machine Learning 3. Big Data Analytics 4. Statistical Modeling and Probability 5. Predictive Analytics 6. Data Visualization and Ethics[1][2][3]
Program Specializations:
Machine Learning
View the exact, up-to-date curriculum on the official program website
Typical Admissions Requirements
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
Academic Requirements (Typical)

• Degree Required: Bachelor’s degree
• GRE/GMAT: Optional
• TOEFL/IELTS: Required for international students (TOEFL 90+ / IELTS 7+)[1]

Application Materials (Typical)

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

Application Timeline

Most programs have rolling admissions or deadlines in early winter for fall admission. Check the official program website for exact dates.

Check Application Deadlines
Career Opportunities in AI

Lead as Data Scientist in Cross-Industry AI with machine learning expertise

Estimated Industry Salary
Data Scientist: $120,000
Total compensation (entry to mid-level)
AI Job Growth
36.0%
Projected 2024-2034 (BLS)
Common Career Paths:
1. Data Scientist 2. Machine Learning Engineer 3. Data Analyst 4. Business Intelligence Analyst
Top AI Employers (Industry-Wide):
Top employers include tech giants like Google, Amazon, Microsoft, and consulting firms such as McKinsey and Deloitte.
Explore AI Career Paths
Program Details
Duration
  • 2 Year
Tuition
  • 67,724
Format
On-Campus
Specializations
Machine Learning
Official Resources
Program Website
Request Information