Business Analytics for Leaders
Program Details
About This Program
Business analytics, including machine learning and artificial intelligence, has game-changing potential in every industry. However, significant barriers exist for leaders wishing 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.
Learn how you can customize this program for your organization.
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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 the Professor of Information and Decision Sciences at the Carlson School of Management. He holds the Carolyn I. Anderson Chair in Business Education Excellence.
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 Managing Director, Carlson Analytics Lab, Carlson School of Management, University of Minnesota. Ellen manages the experiential learning component of the Carlson School’s Master of Science in Business Analytics (MSBA) program. In the Carlson Analytics Lab, student-led teams solve real problems for corporate clients leveraging data analytics tools and techniques.