MS in Data Analytics and Visualization Curriculum

As you progress through the Katz School’s 30-credit MS in Data Analytics and Visualization program, you will develop a work-ready portfolio of projects and deepen your understanding of the core principles, patterns, and practices of data science and visualization. The MS can be completed in as quickly as 12 months, or part time at a pace that makes sense for you. To earn your degree, you must complete 21 credits of required foundational courses, including a capstone project, as well as nine elective courses, which may include an internship.

View typical course sequences for full-time or part-time students.

Core Requirements (21 credits)

Course Credits
Analytics Programming 3
Computational Math and Statistics 3
Project Management for Data Science 3
Spreadsheet Modeling and Analytics 3
Structured Data Management 3
Visual Design and Storytelling 3
Capstone 3

Electives (select 9 credits)

Course Credits
Data-Driven Organizations 3
Data Product Design 3
Data Science 3
Information Architectures 3
Talent Analytics 3
Independent Study 1–3
Internships 1–3
Special Topics 1–3

Bridge Workshops

All admitted students are eligible to get a jumpstart on their programs by taking the free, online bridge workshops starting in May 2018. These three-week courses will enhance skills in math, statistics, spreadsheets, databases, and programming.

  • Database Fundamentals: Learn SQL basics. Work with MySQL and SQL Enterprise Manager to write basic queries, join tables, and design small databases. (May 2018)
  • Math Fundamentals: Refresh fundamental concepts in math and statistics for data analysis including probability, statistics, logarithms, linear algebra, and calculus. (June 2018)
  • Spreadsheet Basics: Create pivot tables, charts, and dashboards with real-world datasets. (July 2018)