AI Practitioner Course:

Based on the four-step process outlined in the book The AI Factor, this course delves into understanding the four quadrants of AI application.  It also explores the data readiness framework, the prioritization value and performance indicators, and the “AI Flywheel” concept. The course focuses on the practical application of these concepts to real-world business scenarios.  This will help participants prioritize and position them for effective implementation.

Course Outline: AI Practitioner

Module 1: Analyzing Business Quadrants

• Identifying Your Organization's AI Type
• Tailoring AI Projects to Business Priorities
• Workbook Exercise: Determining Your Organization's Quadrant

Module 2: Mastering Data Readiness

• Assessing the State of Your Organization's Data
• Overcoming Data Silos and Structuring Unstructured Data
• Workbook Exercise: Assessing Data Readiness for a Single Project

Module 3: Prioritization Techniques

• Aligning AI Projects With Organizational Types
• Selecting High-Priority AI Projects
• Workbook Exercise: Prioritizing AI Initiatives

Module 4: Sustainable, Responsible, and Ethical AI

• Principles of Ethical AI: Privacy, Bias, Transparency
• Workbook Exercise: Addressing Sustainability in Your AI Project

Module 5: Understanding AI Implementation

• Identifying and Implementing AI and Data Projects
• Establishing Measurable Project Goals
• Workbook Exercise: Defining Project Parameters

Module 6: Finding and Using the Right People

• Qualifications and Team Composition for AI Projects
• Securing Organizational Buy-In
• Workbook Exercise: Staffing for the Target Project

Module 7: Scalability (The AI Flywheel)

• Planning and Scaling AI Projects
• Framework for Measuring Success
• Workbook Exercise: Production Details and Success Metrics