9 Data Science Books You Can Read for FREE (Legally)

 

Learning Data Science doesn’t have to be expensive. Whether you’re a beginner or an experienced analyst, some of the best books in Data Science, Machine Learning, Probability, and Python are available for free and legally online.

In this blog, I’m sharing 9 powerful Data Science books that can upgrade your skills without spending a single rupee.

Let’s dive in 👇

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1️⃣ Python Data Science Handbook – Jake VanderPlas

This is one of the most practical books for anyone starting with NumPy, Pandas, Matplotlib, and Machine Learning.

✅ Covers:

• NumPy basics

• Data manipulation with Pandas

• Data visualization

• Intro to Machine Learning

👉 Perfect for beginners and intermediate Python users.

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2️⃣ Elements of Data Science – Allen B. Downey

This book focuses on learning Data Science using real-world thinking, not just tools.

✅ You’ll learn:

• Data exploration

• Visualization logic

• Statistical reasoning

• Hands-on Python examples

👉 A must-read for logical Data Science foundations.

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3️⃣ Data Science and Machine Learning: Mathematical & Statistical Methods

If you want to understand the math behind Data Science, this book is gold.

✅ Covers:

• Linear Algebra

• Probability

• Statistics

• Optimization

👉 Ideal for students preparing for ML research.

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4️⃣ Think Bayes – Allen B. Downey

This book teaches Bayesian Statistics using Python.

✅ You’ll master:

• Conditional probability

• Bayesian inference

• Real-life probability examples

👉 Best for those interested in Data Science + Probabilistic reasoning.

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5️⃣ Python for Data Analysis – Wes McKinney

Written by the creator of Pandas, this is the Data Analyst’s Bible.

✅ Learn:

• Data cleaning

• Data transformation

• Time-series data

• NumPy + Pandas deep dive

👉 If you use Pandas, this book is mandatory.

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6️⃣ Manual for Data Science Projects

This book focuses on real-world Data Science workflows.

✅ You’ll learn:

• Problem formulation

• Data pipelines

• Model deployment

• Industry-level best practices

👉 Perfect for freelancers and job-ready learners.

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7️⃣ Foundations of Data Science – Blum, Hopcroft, Kannan

This book builds core theoretical thinking behind Data Science.

✅ Focuses on:

• Algorithms

• Data modeling

• Computational thinking

👉 Best for CS students & competitive exam prep.

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8️⃣ Probability & Statistics for Data Science – Carlos Fernandez-Granda

This book explains statistics in a very clean and applied way.

✅ Topics include:

• Random variables

• Distributions

• Estimation

• Hypothesis testing

👉 A perfect bridge between math & real-world data.

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9️⃣ Introduction to Probability for Data Science – Stanley H. Chan

If probability scares you, this book will make it simple.

✅ You’ll learn:

• Probability from scratch

• Intuition-based learning

• Data-driven examples

👉 Best for beginners in ML & AI.