ENMGT 5930

Last Updated

  • Schedule of Classes - March 17, 2025 8:55AM EDT

ENMGT 5930
Data Analytics

Course information provided by the 2025-2026 Catalog.

Big data is transforming organizations enabling vast improvements in operating efficiency, market identification and segmentation, and many other domains. This course focuses on data collection at all scales, the transformation of that data into knowledge using a variety of data analytic techniques, and the integration of that knowledge into system models for decision-making to better manage organizations. Expertise in R will be developed throughout this course.


Prerequisites REF-FA25/Corequisites REF-FA25 CEE 3040 or equivalent. Corequisites: None.

Last 4 terms offered (None)

Outcomes REF-FA25

  • Develop an ability to manage, analyze, and interpret data.
  • Improve the students' ability to identify, formulate, and solve engineering management problems.
  • Develop the skills and techniques necessary to become an effective problem solver.

View Enrollment Information

Syllabi: none

  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: CEE 4930, CEE 5930

  • 4 Credits Stdnt Opt

  •  4947 ENMGT 5930   LEC 001

  •  
    • TR
    • Aug 25 - Dec 8, 2025

    • Nozick, L

  • Instruction Mode: In Person

    Enrollment limited to: Engineering Management students; others by permission of department from Diana Peppin (dlw259).

  •  4948 ENMGT 5930   DIS 201

  •  
    • F
    • Aug 25 - Dec 8, 2025

    • Nozick, L

  • Instruction Mode: In Person

Syllabi: none

  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: CEE 5930

  • 4 Credits Stdnt Opt

  •  5151 ENMGT 5930   LEC 002

  •  
    • TBA
    • Aug 25 - Dec 8, 2025

    • Nozick, L

  • Instruction Mode: Distance Learning-Asynchronous

    Enrollment limited to: distance learning students. To request a permission number, contact Alexis Vargas (aev45).

  •  5152 ENMGT 5930   DIS 202

  •  
    • TBA
    • Aug 25 - Dec 8, 2025

    • Nozick, L

  • Instruction Mode: Distance Learning-Asynchronous

    Enrollment limited to: distance learning students. To request a permission number, contact Alexis Vargas (aev45).