Python for Data Science: Hands-On and Applied Projects

Learn Data Science from Scratch with Python — Theory, Code, and Real-World Case Studies in a Complete, No-Fluff Guide

Master Python and kickstart your journey in Data Science with real, applied projects.

This eBook was designed for beginners and intermediate-level developers who want to learn Data Science in a practical, guided, and objective way. Across 10 well-structured modules, you'll go from setting up your environment to building predictive models — including case studies and step-by-step exercises.

You will learn how to:

Set up your development environment using Jupyter, VS Code, and essential libraries (NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn);

Collect, clean, and analyze real-world data;

Create impactful data visualizations using Matplotlib and Seaborn;

Apply Descriptive and Inferential Statistics through clear examples;

Build and validate Machine Learning models;

Publish your projects using version control, documentation, and deployment best practices.

Perfect for those who want to:

Transition into Data Science with a strong foundation;

Practice with real-world projects simulating actual industry problems;

Learn from a single, straightforward, and hands-on resource;

Boost their technical portfolio with real projects.

Includes: commented source code, glossary, bibliography, and access to exclusive online content.