Data Science for Beginners

Data Science sounds difficult, but you can learn it one small step at a time. This beginner-friendly guide takes you from "What is data?" to building your own prediction model, in simple English with plenty of examples.

You will learn Python, clean real data, draw charts and train a model that predicts student marks. Every topic has working code, a line-by-line explanation and sample output, so you always know what is happening and why.

What's inside:

Chapter 1: Introduction to Data Science. Applications, the project lifecycle and a real-world example.

Chapter 2: Python Fundamentals. Variables, lists, dictionaries, loops and functions.

Chapter 3: Pandas and NumPy. Read CSV files, fix missing values and remove duplicates.

Chapter 4: Data Visualization. Bar, line and pie charts and histograms with Matplotlib and Seaborn.

Chapter 5: Machine Learning. Scikit-learn, train-test split, evaluation and a complete mini project.

Extras:

Practice exercises and key takeaways in every chapter

Colorful illustrations, tables and ready-to-run code

Glossary, common-error fixes and a learning roadmap for what to study next

Perfect for: students, freshers, career changers and anyone curious about data. You only need a computer and the free Google Colab, so nothing to install.

About the book: 42 pages of original content from KK Digital Books.