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Master of Computer Science - Data Science

  1. Description
  2. Application
  3. Curriculum
  4. Tuition

Curriculum: Students must complete one course each (with a grade of B- or higher) from the four different areas of machine learning, data mining, data visualization, and cloud computing.

Machine Learning

  • CS 498 - Applied Machine Learning
Data Mining
  • CS 410 - Text Information Systems
  • CS 411 - Database Systems
  • CS 412 - Introduction to Data Mining
Data Visualization
  • CS 498 - Data Visualization
Cloud Computing
  • CS 425 - Cloud Computing Concepts
  • CS 498 - Cloud Computing Applications
  • CS 498 - Cloud Networking
Must complete three course (12 credit hours)
  • CS 513 - Theory and Practice of Data Cleaning
  • CS 598/IS 531 - Foundations of Data Curation
  • CS 598.STAT 542 - Practical Statistical Learning
  • CS 598/STAT 578 - Advanced Bayesian Modeling
  • CS 598 - Cloud Computing Capstone
  • CS 598 - Data Mining Capstone
Electives - not required, but available to use toward the eight courses required for the degree.
  • STAT 420 - Methods of Applied Statistics

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