Business Analytics for Leaders
Program Details
About the Program
Business analytics, including machine learning and artificial intelligence, has game-changing potential in every industry. Harnessing the power of your data can help you counteract the increasing complexity of business operations, global competitive forces, and industry disruption.
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, recommended by Fortune, will demystify analytics, walk through use cases in a variety of industries and business functions, and ultimately teach you how to become an analytics champion at your organization.
Learn how you can customize this program for your organization.
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Program Contact
- Email: croeckle@umn.edu
- Phone: 612-625-5412
- REQUEST COURSE CATALOG
Audience
- Leaders across all functional areas including marketing, finance, information systems, operations and HR with P&L
- Managers with significant project/functional responsibility
- No prior technical analytics expertise is needed
Key Benefits
- 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
Schedule
Exploratory Analytics Using Data Visualization (Level 1)
Managing Successful Analytics Projects
Predictive Analytics Using Machine Learning (Level 1)
Causal Inference using Existing Data
Deploying Analytics Workshop
Strategies for Deploying Analytics in Your Organizations
Advanced Predictive Analytics
Explainability of Black Box Models
Dealing with Fairness and Bias Issues in Machine Learning
Additional Details
Faculty
Gedas Adomavicius is a professor in the Department of Information and Decision Sciences at the Carlson School of Management, University of Minnesota, where he also holds the Larson Endowed Chair for Excellence in Business Education.
Professor Ravi Bapna's expertise lies in helping companies reframe their understanding of analytics, AI, and machine learning, and then leverage that understanding for competitive advantage.
Ellen Trader is the Assistant Dean and Chief Learning Officer for Carlson Executive Education, Carlson School of Management, University of Minnesota. Ellen works with faculty to provide transformative learning opportunities for individuals, teams, and organizations.