Data Science and Analytics, M.S.

Program Overview

  • 50% computing and 50% statistical courses ensure comprehensive data science education
  • Hands-on experience with Python, R, data engineering, and machine learning models
  • Expertise in data visualization, statistical modeling, and machine learning-based analytics
  • Focus on internships, real-world projects, and career readiness in data science fields
  • Professional Science Master’s Program
    • Industry-focused curriculum blending advanced technical skills with professional development for leadership in data science

Coursework

The Data Science and Analytics program blends data science with courses in statistics and the professional science master's program. Key concepts in the curriculum include:

  • Data engineering and mining
  • Information visualization
  • Statistical modeling
  • Ethics and professionalism

 

Curriculum Guide Advising Plans  Course Descriptions  

Program Overview

Data Science and Analytics


Final Internship

All DSA students must complete an internship as part of their Professional Science Master's curriculum. More information on finding an internship and getting credit for it is at our PSM website.

Please contact Professor Holli Reyes and/or Professor Anirudh Chowdhary for assistance in resume building, interviewing, and resources.


Not Admitted Yet? Apply Now!


Page last modified November 15, 2024