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Description

Apply Python and statistical thinking to evaluate trends, assess performance and communicate insights for business operations.

Outline

The Data Analytics for Decision Support course explores applied data analysis methods essential for assessing performance, identifying trends and evaluating operational impact. Learners will build a strong conceptual foundation in statistical thinking, enabling them to formulate analytical approaches that drive informed decision-making in business operations. By focusing on evaluative questions, participants will learn how to accurately describe trends, contextualize changes and thoughtfully interpret data to enhance the overall value and impact of their analytical work.

Transitioning from theory to practice, the course emphasizes implementing these analytical concepts using Python. Learners will develop their coding skills to generate summary statistics and conduct hypothesis testing. They will create insightful data visualizations that uncover patterns and deviations to support implementation planning. Ultimately, learners will be equipped to conduct exploratory applied program evaluations, summarizing their results and responsibly communicating their findings while critically acknowledging the limitations of their chosen analytical methods.

Course Outcomes

By the end of this course, participants will be able to:

  • formulate analytical approaches to describe and understand trends.
  • apply statistical thinking to evaluative questions regarding trends and contextualize changes to these trends.
  • implement statistical methods for analysis in Python, including the generation of summary statistics and hypothesis testing to identify patterns and deviations.
  • conduct exploratory applied program evaluations in Python while using appropriate methods, summarizing results and communicating findings responsibly given limitations of methods

Course Format

This six-week course blends elements of asynchronous and synchronous components to provide learners with flexibility in project work, while also having face-to-face time with instructors and fellow learners via Zoom. 
Each week, learners will:

  • attend one 90-minute Zoom, during which students will participate in discussions and workshop their project with the instructor and peers
  • complete three to four hours of assignments or project work

Learners will be graded based on completion of assessed assignments/projects.

Testimonials

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Applies Toward the Following:

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Section Title
Data Analytics for Decision Support
Type
Online, instructor led
Dates
May 17, 2027 to Jun 27, 2027
Delivery Options
Instructor Led Online  

Section Details

Contact: 612-625-2900 or ccapsreg@umn.edu

Zoom course meetings are 12:00–1:30 pm US Central Time on: 

  • Wednesdays: May 19, 26, Jun 2, 9, 16, 23
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