Predictive Analytics Essential Training for Executives

Introduction

• Give yourself the executive analytics edge
• Our course goals

1. Identifying the Optimal Type of Analytics for Your Challenge

• Predictive analytics vs. forecasting
• AI compared to predictive analytics
• What is traditional or classic machine learning?
• Predictive analytics compared to statistics and data science
• Can Gen AI and LLMs be used in predictive models?

2. Getting Serious about Analytics

• Analytics is about making decisions
• Propensity scores and business problems
• The unintended consequences of proof of concept projects
• Why deployment, not insight, is the primary goal
• Analytics as a profit center

3. Hiring and Staffing

• Who should you hire first for your new data science team?
• Data scientist, data engineers, and MLOps
• Data science job requirements and the problems they can create
• Growing a team organically
• Data scientists with and without vertical industry experience
• The importance of SMEs to modeling
• Do you need the latest new techniques?
• How to spot potential

4. Software and Technology

• Cloud and enterprise analytics
• Why data prep has to be customized for predictive models
• The analytics software ecosystem
• Citizens and self-service
• Responsible AI

5. Organizational Structure

• Analytics project management
• Career path of the data scientist
• Who should data science report to?
• The role of the CAO
• CAOs, CDOs, and CAIOs

6. Continuing Your Predictive Analytics Learning Journey

• Next steps and additional resources