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A Manager’s Guide to Business Analytics and Machine Learning with AI: Directing the Business Analytics Process

Business Analytics

ISBN #978-1-967084-64-7

A Manager’s Guide to Business Analytics and Machine Learning with AI: Directing the Business Analytics Process

Mark Keith, PhD
Thomas Meservy, PhD

This book prepares managers to direct analytics work from the business question through deployment. Students use AI to generate code, but they learn enough to read it, test it, and decide whether the result deserves trust. Organized around CRISP-DM, the book connects data preparation, modeling, evaluation, communication, governance, and project economics to the decisions senior leaders actually make.

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Table of Contents

Foreword: Analytics Leadership
Chapter 1: Business Analytics
Chapter 2: AI Analytics Leadership
Chapter 3: Reading Python
Chapter 4: Verifying AI Code
Chapter 5: CRISP-DM
Chapter 6: Univariate Exploration
Chapter 7: Data Cleaning
Chapter 8: Bivariate Exploration
Chapter 9: Feature Engineering
Chapter 10: Causal Regression
Chapter 11: Predictive Regression
Chapter 12: Classification Decisions
Chapter 13: Analytics Deployment
Chapter 14: Analytics Strategy
Chapter 15: Responsible Analytics
Chapter 16: Capstone Project
Supplement: Datasets

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