Undergraduate Catalog 2024-2025

BUSA 3580 Computational Thinking in Business

This course introduces students to various business analytics applications, cases and software tools to help understand, interpret, and visualize business data and valuable patterns in big data. Topics include; data acquisition, data cleaning, storage and retrieval, data analysis, and production product development. The course will use the programming language Python and the R statistical package as the primary software tools.

Registration Name

Computational Thinking for Bus

Lecture Hours

3

Lab Hours

0

Credits

3

Prerequisite

none

Offered

Demorest: even Spring

Student Learning Outcomes

At the successful completion of this course, students will be able to:

  • Select appropriate statistical methods and programming tools to address the business problem
  • Conduct statistical analysis using selected software tools
  • Organize structured and unstructured data for analysis.
  • Program repetitive and specialized functions
  • Use machine learning techniques for model building
  • Use data visualization techniques for presenting results
  • Identify common mistakes and biases that skew analysis results