MS in Data Analytics Curriculum Plan


Curriculum Plan (2020-2021)

Please note that there may be other requirements for completion or options for elective and specialized courses. Please see the academic catalog for the full curriculum. Course offerings and sequence are subject to change.

For Students with Undergraduate Majors not including a basic course in math, a course in statistics and a course in programming. Prerequisite courses should be completed during Session 1 and 2 of Year One.

Prerequisite Courses

  • Essentials of Computational Science Using Python
  • Basic Applied Statistics


  • Foundations of Data and Decision Algorithms
  • Database Design Principles and Technologies
  • Architectures and Methods for Data Mining
  • Strategy and Financial Planning in Global Contexts
  • Big Data Tools
  • Data Analytics and Decision Making
  • Advanced Programming with Python
  • Professional Practice (3 required courses in total)
  • Data Visualization
  • Management & Marketing Models for Managerial Decision Making
  • Industry Research Project

Instruction may be provided on-ground, online or in hybrid modalities, and varies by program. For on-ground and hybrid programs, instruction is primarily provided at an Alliant campus; however, some instructional activities may take place off campus at a location appropriate for the particular activity, including, but not limited to, online courses or online portion of courses, internships, practicums, or field placement activities.

For online programs, instruction is provided online; however, some programs may include an in-person residency requirement at one of Alliant’s campuses. Additional instructional activities, including, but not limited to internships, practicums, or field placement activities may take place at a location appropriate for the particular activity.


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