Business Analytics for Leaders
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Learn how machine learning and artificial intelligence can propel insight discovery, informed decision-making, and rapid action.
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).
- 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
- Statistical Principles and A/B Testing for Business Analytics
- Exploratory Analytics Using Maching 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.)
- 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
- Deployng Analytics workshop (part 2)
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 learning to 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