AI DATA ANALYTICS USING PYTHON

In today’s world, data is rapidly becoming the most valuable
asset across industries. From business to healthcare, technology to
finance, organizations are leveraging the power of data to gain insights,
make informed decisions, and predict future trends. This paradigm shift
has led to the need for robust tools and methodologies to manage and
analyze vast amounts of data—leading us into the age of Big Data and
Artificial Intelligence (AI).
This book, AI Data Analytics Using Python, serves as a
comprehensive guide for individuals and professionals eager to learn
how to harness the power of data using one of the most versatile and
widely used programming languages: Python. Python’s simplicity,
versatility, and wide ecosystem of libraries make it the go-to language
for data analysis, machine learning, and AI.
The primary aim of this book is to provide both the theoretical
understanding and practical applications of data analytics, machine
learning, and AI, using Python and cutting-edge technologies such as
Apache Spark, PySpark, and various data science and deep learning
libraries. Whether you are a beginner or an experienced data scientist,
this book is designed to offer you a well-rounded understanding of the
tools and techniques that power modern data analysis workflows.
We begin with an introduction to large-scale data analysis,
diving into the importance of Big Data, the components of Apache
Spark and PySpark, and how they revolutionize data processing at scale.
Through successive chapters, we explore key data analytics concepts,
including data preparation, statistical analysis, anomaly detection, time
series analysis, and more. Each concept is explained in a simple yet

detailed manner, supplemented with Python code examples and step-
by-step instructions that you can follow to replicate real-world data analysis tasks.