Fundamentals of Data Science: Take the first Step to Become a Data Scientist (Step-by-Step Tutorial For Beginners)

Gain an understanding of the foundations of data science and its applications. This short book does not require technical abilities or cover how to code. The author focuses on nontechnical skills, such as the management of data science implementation efforts. This book is recommended for beginners and anybody who want to understand Data Science in an easy way. You don’t need a big textbook to master Data Science today.
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Book Objectives

This book is an introduction to data science with the following objectives:

To help you understand the correct meaning of data science.
To help you understand the various fields that make data science.
To familiarize you with various algorithms used in data science.
To introduce you to the most popular data science software tools.
To help you understand the best languages for data science tasks.
To help you know where and how you can apply data science in your business.

Who is this Book is for?

Here are the target readers for this book:

Anybody who needs to familiarize themselves with the fundamentals of data science..
Anybody who needs a thorough introduction to data science before venturing into its practicalities..
Anybody who needs to know where and how they can apply data science in their business.
Professionals in data science, computer programming, computer scientist.
Professors, lecturers or tutors who are looking to find better ways to explain Data Science to their students in the simplest and easiest way.
Students and academicians, especially those focusing on Data Science, Computer Science, Neural Networks, Machine Learning, and Deep Learning.
Anybody who needs to understand the various approaches, tools, and theories underlying data science.

What do you need for this Book?

The author expects you to have a computer installed with an operating system such as Linux, Windows or Mac OS X. And you are required to have installed the following on your computer:
Python 3.X
Numpy
Pandas
Matplotlib

The Author guides you on how to install and configure the rest of the Python libraries that are required for data analysis.

What is inside the book?

BASICS OF DATA SCIENCE
DECISION THEORY
ESTIMATION THEORY
COORDINATE SYSTEMS
LINEAR TRANSFORMATION
GRAPH THEORY
ALGORITHMS
MACHINE LEARNING
DATA COLLECTION, MODELLING, AND COMPILATION
DATA ANALYSIS
DATA PRESENTATION AND VISUALIZATION
DATASCIENCE SOFTWARE TOOLS
PROGRAMMING LANGUAGES FOR DATA SCIENCE
APPLICATIONS OF DATA SCIENCE.