The data analytics program is housed in the Department of Electrical Engineering and Computer Science and offered in partnership with other departments at the University, including Mathematics, Library & Information Sciences, and the Busch School of Business. The program is intended for those with backgrounds outside of computer science, such as in business, engineering, healthcare, or physical or social sciences. Students are taught to use computer science, statistics, machine learning, visualization, and human-computer interactions to collect, process, analyze, visualize, and interact with data from their domain of expertise to create useful knowledge.

credit-hours-300.svg  Credit Hours: 30 credits
  Tuition: $1,250 per credit hour
cirriculum-300.svg  Curriculum:


Consisting of 3 fundamental core courses, 6 program elective courses, and a 3-credit capstone practicum selected from an approved set of challenge areas developed in partnership with industry, government, and civic organizations. Students may receive data sets from partners or public domain to complete a project which involves processing and analyzing the data set to address a specific problem.

  • DA core courses (all required)

    • DA 501: Introduction to Data Science and Python (3 credits)
    • DA 514: Applied Statistics and Data Analysis (3 credits)
    • DA 515: Introduction to Machine Learning (3 credits)
    • DA 591: Data Science and Analytics Practicum (3 credits)

  • DA program electives (6 required)

    Most of the elective courses are offered once a year depending on the availability of faculty.

    • DA 503: Data Visualization with Tableau (3 credits)
    • DA 505 Decision Analysis (3 credits)
    • DA 509: Web Design & Programming (3 credits)
    • DA 516: Applications of Data Analytics and Development (3 credits)
    • DA 523: Business Data Analytics (3 credits)
    • DA 527: Fundamentals of Neural Networks (3 credits)
    • DA 529: Introduction to Computer Vision (3 credits)
    • DA 542: Introduction to Database Management (3 credits)
    • DA 545: Introduction to Data Mining (3 credits)
    • DA 575: Introduction to System Analysis (3 credits)
    • DA 580: Numerical Analysis and Optimization (3 credits) 
    • LSC 633: Information Retrieval and Analysis (3 credits)
    • LSC 653: Data on the Web (3 credits) 
    • ECON 570: Big Data for Economics (3 credits)
    • Others  
apply icon