• ENTP 3501

    Business Essentials, Reflections, and Virtual Applied Micro Internship
     Rating

     Difficulty

     GPA

    Last Taught

    Summer 2025

    Students must first complete several self-paced asynchronous modules called Business Essentials, which cover introductory content in marketing, finance, strategic management, and accounting. Students will also engage in online synchronous coursework and write reflections on the psychology of decision-making, influencing, and teamwork. Concepts from both the online modules and coursework will be applied to a virtual, team-based micro internship.

  • GSGS 3550

    Topics in Global Studies
     Rating

     Difficulty

     GPA

    Last Taught

    Spring 2026

    Various topics offered in Global Studies. See department website for full course descriptions. 

  • CGBM 3559

    Topics for General Business Minor
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     Difficulty

     GPA

    Last Taught

    Spring 2025

    New Course in Commerce, specifically designed for the General Business minor degree program.

  • LPPS 3724

    Just Policy: Justice, Goodness, & Public Policy
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     Difficulty

     GPA

    Last Taught

    Spring 2025

    Course explores the integration of moral & ethical considerations in addressing U.S. public policy challenges. Students study & contrast major philosophical & political theories of justice & the common good, including those that are embedded in the U.S. constitutional architecture; and consider and contrast how these theories would guide public policy choices.

  • PSHM 3805

    Health Information Systems and Applications
     Rating

     Difficulty

     GPA

    Last Taught

    Spring 2026

    Introduces foundational knowledge and emerging trends in health informatics, and examines how information systems can be utilized to improve patient care, health outcomes, efficiency, and quality. Provides knowledge on how health informatics can enhance evidence-based decision making, cost-management, and performance; analyzes key issues in data management, and confidentiality in health informatics. Prerequisite: Admission to BPHM or BIS Program.

  • UNST 3910

    Internship Reflection: Self & Organizations
     Rating

    3.33

     Difficulty

    1.00

     GPA

    Last Taught

    Spring 2026

    This course is focused on an exploration of "self" in relationship to the complexities and structures of the professional organizations in which students work as interns. The course combines organizational behavior concepts and content that emphasizes self and exploration.

  • UNST 3920

    Internship Reflection: Teams, Leadership, & Organizations
     Rating

     Difficulty

     GPA

    Last Taught

    Spring 2026

    The course is focused on an exploring the dynamics of teams and leadership within the complexities and structures of the organizations in which students work in professional practice internships. The course combines organizational behavior with concepts of teams and organizations.

  • EDNC 3986

    Youth and Social Innovation Internship
     Rating

     Difficulty

     GPA

    Last Taught

    Spring 2026

    Students apply academic experiences in professional and/or research settings; reflect and critically and constructively analyze experiences from multiple perspectives; and view the work as connecting course content authentic contexts. Students work as professionals with site supervisors and instructors to complete related assignments and relevant background research on the professional and academic resources available.

  • ARCY 3993

    Independent Study
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     Difficulty

     GPA

    Last Taught

    Spring 2026

    An Independent Study in Archaeology. Subject to be determined by student and instructor.

  • DS 4021

    Analytics II: Machine Learning
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     Difficulty

     GPA

    Last Taught

    Fall 2025

    Critique models and adapt them to a variety of data sets. Gain a deeper understanding of core ML concepts. Build towards neural networks (latent index models, more complex linear models with non-linear transformations of the data). Compare new methods to kNN, clustering, linear models from ML1 to discuss performance differences as complex and predictive power increases. How mathematical concepts are present in the models presented.