MS in Applied Data Science for Business

The Master of Science in Applied Data Science for Business (MSADSB) focuses on the needs of business leaders to understand digital transformation and the importance of data science across functional areas. In addition to the core curriculum, students must complete at least one approved certificate plus additional credits from any of the other approved certificates or electives to complete a minimum of 45 credits.

The core curriculum imparts the business fundamentals of accounting and strategy; the critical business implications of digital transformation and the organizational change that it will necessitate; the regulatory, ethical, and cybersecurity imperatives governing digital transformation; and an introduction to technical skills.

  • Full Time: 12 Months
  • Part Time: 24 Months

Core Curriculum (22 - 24 credits)

  • Digital Transformation of Business: MGMT 518 (4 credits)
  • Digital Transformation: Security, Privacy & Ethics: MGMT 519 (4 credits)
  • Leading Organizational Change During Digital Transformation: MGMT 520 (4 credits)
  • Special Topics in Data Science, Technology for Business: Data Structures for Business Applications: ISQA 522 (2 credits)
  • Special Topics in Data Science: Machine Learning Applications for Managers: ISQA 523 (2 credits)
  • Managerial and Cost Accounting: GSCM 512 or Managerial Accounting and Control: ACTG 513 (4 credits)
  • Foundations of Strategy: MGMT 511 (2 credits)
  • Data Visualization: ISQA 521 (2 credits) (Required in core if there isn't a data visualization course in your chosen certificate)

Certificate Specialization + Electives (21-23 credits)

The certificates approved for this master’s program are:

Certificate Option 1: Business Blockchain (18 credits) + Electives (3 credits)

Prerequisites: Basic Database & Distributed Ledger Concepts* (No credit: Pass/No Pass)

  • Blockchain Fundamentals: ISQA 581 (4 credits)
  • Blockchain Fundamentals Lab: CS 510 (2 credits) 
  • Blockchain in Business: ISQA 583 (4 credits)
  • Blockchain in Business Lab: ISQA 584 (2 credits)
  • Blockchain Uses and Applications: ISQA 585 (4 credits)
  • Emerging Topics in Blockchain: ISQA 586 (2 credits)

Certificate Option 2: Business Intelligence and Analytics (21 credits) + Electives (2 credits)

Prerequisites: Statistics Primer (No credit: Pass/No Pass) or STAT 451/551 or STAT 461/561* 

  • Operations Research Management Science: ETM 540 (4 credits)
  • Applied Regression Analysis: ISQA 516 or Regression Analysis: STAT 564  (3 credits) 
  • Decision Support Systems: Data Warehousing: ETM 538 (4 credits)
  • Data Mining with Information Theory: SYSC 531 (4 credits)
  • Intro to Business & Analytics: ISQA 520 (4 credits)
  • Data Visualization: ISQA 521 (2 credits)

Certificate Option 3: HR Analytics (18 credits) + Electives (5 credits)

Prerequisites: Basic HR Management & Statistics Concepts Primer (No credit: Pass/No Pass)

  • Introduction to HR Analytics: MGMT 541 (4 credits)
  • Special Topics: Asking HR Questions, Telling HR Stories: MGMT 548  (2 credits) 
  • HR Analytics Tools and Applications:MGMT 542 (4 credits)
  • Data Mining with Information Theory: SYSC 531 (4 credits)
  • Intro to Business & Analytics: ISQA 520 (4 credits)
  • HR Data Visualization & Storytelling: MGMT 553 (2 credits)

Visit the 2020-2021 Bulletin for course details.

Sample schedule coming soon.

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