فهرست مطالب

• Preface
• 1. Analytical Thinking and the AI-Driven Enterprise
• What Is AI?
• Why Current AI Won’t Deliver on Its Promises
• How Did We Get Here?
• A Tale of Unrealized Expectations
• Analytical Skills for the Modern AI-Driven Enterprise
• Key Takeways
• Further Reading
• 2. Intro to Analytical Thinking
• Descriptive, Predictive, and Prescriptive Questions
• Business Questions and KPIs
• An Anatomy of a Decision: A Simple Decomposition
• A Primer on Causation
• Uncertainty
• Key Takeaways
• Further Reading
• 3. Learning to Ask Good Business Questions
• From Business Objectives to Business Questions
• Descriptive, Predictive, and Prescriptive Questions
• Always Start with the Business Question and Work Backward
• Further Deconstructing the Business Questions
• Learning to Ask Business Questions: Examples from Common Use Cases
• Key Takeaways
• Further Reading
• 4. Actions, Levers, and Decisions
• Understanding What Is Actionable
• Physical Levers
• Human Levers
• Revisiting Our Use Cases
• Key Takeaways
• Further Reading
• 5. From Actions to Consequences: Learning How to Simplify
• Why Do We Need to Simplify?
• Exercising Our Analytical Muscle: Welcome Fermi
• Revisiting the Examples from Chapter 3
• Key Takeaways
• Further Reading
• 6. Uncertainty
• Where Does Uncertainty Come From?
• Quantifying Uncertainty
• Making Decisions Without Uncertainty
• Making Simple Decisions Under Uncertainty
• Decisions Under Uncertainty
• Normative and Descriptive Theories of Decision-Making
• Some Paradoxes in Decision-Making Under Uncertainty
• Putting it All into Practice
• Revisiting Our Use Cases
• Key Takeaways
• Further Reading
• 7. Optimization
• What Is Optimization?
• Optimization Without Uncertainty
• Optimization with Uncertainty
• Key Takeaways
• Further Reading
• 8. Wrapping Up
• Analytical Skills
• The AI-Driven Enterprise of the Future
• Some Final Thoughts
• A. A Brief Introduction to Machine Learning
• What Is Machine Learning?
• A Taxonomy of ML Models
• Regression and Classification
• Making Predictions
• From Linear Regression to Deep Learning
• A Primer on A/B Testing
• Further Reading
• Index