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Business Analytics for Leaders

Learn how machine learning and artificial intelligence can propel insight discovery, informed decision-making, and rapid action. 

This course runs every fall. Dates subject to change.

About This Program

Business analytics, including machine learning and artificial intelligence, has game-changing potential in every industry. However, significant barriers exist for executives to harness these emerging forces into their management practice. Companies that successfully develop advanced capabilities to leverage their data can make quicker, faster, and more informed decisions across all areas of their firms, creating a significant competitive advantage. This course will transform leaders into analytics champions within their organizations and help fuel data-driven cultures.

To learn more about this program, download the brochure or reach out to Carol Roecklein at croeckle@umn.edu or at (612) 625-5412.

Program Details
Cost: $4500.00

The program has helped me understand how to turn all this transactional data that I deal with on a day-to-day basis into an asset for my clients and my company.


This is a fantastic introduction to a fast moving area.  Data Analytics, Machine Learning, and AI will touch us all.  I now have the understanding to guide my organization to embrace the opportunities of this rapidly evolving area.  Well worth three days.


Business Analytics for Leaders

Navigate the sea of data to drive insights, informed decisions and rapid action. This course will transform leaders into analytics champions within their organizations and fuel a data-driven culture.

Additional Details

Day 1

  • Winning with Data Analytics - The Four Pillars
  • Exploratory Analytics - Level 1 - Data Visualization
  • Predictive Analytics - Level 1 - Using Machine Learning
  • Communicating Data and Analytics
  • Managing Successful Analytics Projects

Day 2

  • Statistical Principles and A/B Testing for Business Analytics
  • Exploratory Analytics Using Machine Learning-Level 2
  • Predictive Analytics Using Machine Learning-Level 2
  • Deploying Analytics Workshop (Part 1)
  • Networking Reception with Industry Experts (5:30 - 6:30 p.m.)

Day 3

  • Advanced Issues in Exploratory and Predictive Analytics Using Machine Learning
  • Machine Learning at Big Data Scale
  • Unstructured Data Analytics: Text Mining
  • Organizational Design Issues and Talent Strategies
  • Deploying Analytics workshop (part 2)

Schedule subject to change.

Leaders across all functional areas including marketing, finance, information systems, operations and HR with P&L or significant project/functional responsibility will benefit from this course. No prior technical expertise is needed. 

This program has value across a broad range of industries. Applications include, but are not limited to: retail (store layout optimization); banking (loan default prediction); consumer products (advanced customer segmentation); medical (product feature optimization).

In this interactive course leaders will:

  • Learn how to build organizational capabilities to leverage machine learning and artificial intelligence for competitive advantage. Explore the Carlson School’s Four Pillars of Analytics approach that integrates causal, exploratory, predictive and prescriptive analytics
  • Understand the transformative power of today’s analytics, including the broad scope of business questions that can now be answered
  • Learn how to unlock hidden insights with data - using descriptive, predictive and prescriptive approaches - to support faster, more effective decision-making
  • Gain foundational insight into new machine learning methods to predict future outcomes, e.g., customer churn, optimal product mix
  • Directly apply learnings to a real-world application during daily use case discussions
  • Increase communication skills and ability to partner with Analytics and IT teams
  • Learn best practices, including structured problem solving, in deploying analytics projects
  • Begin scoping analytics projects, utilizing the Carlson Analytics Lab framework
Contact Carol Roecklein

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