This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning. It consists of three parts. The first is an overview of the history of artificial intelligence, machine learning, and data science, and also includes case studies of well-known AI systems. The second is a step-by-step introduction to Azure Machine Learning, with examples provided. The third is an explanation of the techniques and methods used in data visualization with R, which can be used to communicate the results collected by the AI systems when they are analyzed statistically. Practice questions are provided throughout the book. Sample Chapter(s) Preface Chapter 1: Summary of Artificial Intelligence Request Inspection Copy Contents: Artificial Intelligence: Summary of Artificial Intelligence Machine Learning Deep Learning Case Study Microsoft Azure Machine Learning Studio Create Prediction Model using Microsoft Azure Machine Learning Studio Create Prediction Model using Microsoft Azure Machine Learning Studio Web Service Deployment Creating a Prediction Model using Microsoft Azure Machine Learning Studio Script Integration Exercises: Exercises Visualization: Visualization Visualization with Power BI Visualization with R in Power BI Readership: Students of artificial intelligence and engineers working in artificial intelligence.