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ions 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. Get your copy now!!Book ObjectivesThis 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 python for data analysis to their students in the simplest and easiest way.
• Students and academicians, especially those focusing on python programming, 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.

The author has discussed everything that you need to know about data science. First, you are guided to learn the meaning of data science. The history of data science has been discussed to help you know how people came to realize that data is a rich source of knowledge and intelligence. The theories underlying data science have been discussed. Examples include decision and estimation theories. The author has discussed the various machine learning algorithms used in data science. The various steps one has to undergo when performing data science tasks have been discussed from data collection to data presentation and visualization. The author helps you know the various ways through which you can apply data science in your business for increased profits. A simple language has been used to ensure that there is ease of understanding, especially for beginners.