This book was created (recorded, written, and many times revised) for a wide variety of students because that is who I teach. Although I am a professor of Information Systems in the school of business at a large university, this topic has attracted students from every background. And truthfully, the topic of data science applies to every discipline that I can imagine. Therefore, I have tried to select examples and demonstrations from a wide variety of topics as well.
The purpose of this course is to be an initial exposure to the field of data science. You will learn the methodology, or process, used to take an idea/opportunity/problem from data collection to predictive model deployment. In other words, you will not only learn high level concepts, but also the detailed skills needed to truly understand how to leverage the power of data for predictive machine learning deployment.
This particular version of the book is intended for students who want to learn advanced applications without getting too deep into a programming language like Python, Julia, or R. Rather, this book uses Tableau for data visualization and some limited Excel for a few of the tasks requried during exploratory data analysis. However, the primary tool used to create and deploy machine learning pipelines is Microsoft's Azure Machine Learning Studio.
As a result, this book is perfect for a wide variety of students from undergraduate to graduate levels. This version of the book also includes a primer on Relational Databases and Structured Query Language (SQL) for students who do not already have that background. If you don't need that content and would like a greater focus on deploying machine learning pipelines in web appliations, you may prefer the version titled "Data Analytics and Machine Learning". Also, if you are looking to learn a more technical skillset for a full-time "data scientist" role, then I suggest using either "Introduction to Python Data Analytics" or "Machine Learning in Python and Azure" which teach the same principles, but based primarily on Python programming as opposed to "click-and-drag" tools. Each of those versions of this book are available on the MyEducator.com platform.