Degree Requirements

Overall Degree Learning Outcomes

  • Analyze and interpret data critically using statistical models and programming skills.
  • Effectively communicate results of analyses to both the expert and layperson.

Course Requirements (36-38 hr)

Core Courses (18-19 hr)

Select 1 of the following (3-4 hr):

  • Mathematical Foundations of Data Analytics (MTH 133) offered during academic year
  • Basic Math for Analytics (ISA 250) offered only during summer

Select 1 of the following (3 hr):

  • Introduction to Statistical Modeling (STA 363)
  • Applied Regression Analysis in Business (ISA 291)
  • Applied Research Methods (POL 306)

Take all of the following (12 hr):

  • Professional Communication for Data Analytics (ENG/STC 285)
  • Data, Ethics, and Society (PHL/HST/GIC 286)
  • Introduction to Programming and Scripting for Data Analytics (STA/POL 308)
  • Building, Managing and Exploring Data Sets in Analytics (STA/POL 209)

Select 1 of the concentrations below. Students may not select multiple concentrations.

Concentrations

Concentration in Geospatial Analytics (18-19 hr)

Learning outcome: Design and execute workflows for geospatial problem solving and analysis.

Select 1 of the following (3-4 hr):

  • Global Forces, Local Diversity (GEO 101)
  • Earth's Physical Environment (GEO 121)
  • Geographic Perspectives on the Environment (GEO 122)
  • Geography of Urban Diversity (GEO 201)
  • Geohazards and the Solid Earth (GLG 261)

Take all of the following (12 hr):

  • Mapping a Changing World (GEO 242)
  • Geographic Information Systems (GEO 441)
  • Advanced Geographic Information Systems (GEO 442)
  • Techniques and Applications of Remote Sensing (GEO 448)

Select 1 of the following (3 hr):

  • Python Programming for Geospatial Applications (GEO 443)
  • Advanced Systematic Geography (GEO 460)

Concentration in Bioinformatics (19 hr)

Learning outcome: Integrate experimental bioinformatics data with biological pathway analysis to achieve understanding in complex biological processes.

Take all of the following (19 hr):

  • Biological Concepts: Structure, Function, Cellular, and Molecular Biology (BIO 116)
  • Introduction to Programming for the Life Sciences (BIO 256)
  • Bioinformatics Computing Skills (BIO 466)
  • Bioinformatics Principles (BIO 485)
  • 6 hr of BIO, MBI, or CHM courses (200-level or above)

Concentration in Sport Analytics (pending final approval) (18 hr)

Learning outcome: Identify and apply appropriate methods of analytics in sporting contexts.

Take all of the following (18 hr):

  • Sport Communication and Media (KNH 273)
  • Introduction to Sport Analytics (KNH 275)
  • Sport Economics and Finance (KNH 313)
  • Sport Marketing (KNH 416)
  • Sport Econometrics (KNH 418)
  • Sport Administration (KNH 472)