Introduction to Python for Computer Science and Data Science by Paul Deitel and Harvey Deitel - Non Fiction - Paperback

Title:
Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud

Condition: BRAND NEW
Format: Paperback

Overview:
Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud offers a fresh, flexible pathway into Python that serves both computer science newcomers and data science explorers. Crafted by The Deitels, this book pairs rigorous programming fundamentals with real-world relevance, so readers don’t just learn to write code — they learn how code drives modern technology. Starting with Python basics—syntax, variables, control flow, and simple data structures—the book gradually builds toward more advanced topics: functions, modules, and object-oriented programming, all presented with clear explanations and plenty of hands-on practice. What truly sets this text apart is its deliberate integration of AI concepts, big data workflows, and cloud-oriented projects. Readers encounter real-world datasets and technologies that mirror industry use, empowering them to build projects that matter in business, government, or academia. The spine of the course is the included Jupyter Notebook supplements, which provide an interactive lab environment to test ideas, run analyses, and visualise results in real time. This paperback is designed for introductory courses and self-guided learners alike, offering a coherent progression from first lines of code to data-driven applications.

What Makes This Book Stand Out:
This book distinguishes itself by uniting computer science foundations with data science practice in a single, approachable volume. The Deitels guide readers through Python with a methodical roadmap that emphasizes conceptual understanding alongside practical application. The text deliberately foregrounds AI, big data, and cloud contexts, ensuring students see the relevance of programming beyond academia. Real-world datasets and machine-learning-inspired exercises transform theory into tangible outcomes, from data cleaning and exploration to simple predictive ideas. The inclusion of Jupyter Notebooks gives learners a hands-on sandbox for experimentation, enabling immediate feedback and iterative learning. The result is a robust, career-relevant introduction that remains accessible to beginners while staying aligned with current industry workflows and tools.

Who This Book Is Perfect For:
This book is ideal for freshmen and sophomores in computer science and data science programs, as well as self-mudents eager to gain practical programming skills with Python. It suits introductory-level courses, tutorials, and bootcamp-style learning paths that aim to blend coding proficiency with data analysis and AI awareness. Teachers and course designers will appreciate its clear structure and project-oriented approach, while students seeking hands-on projects with real-world impact will find ample motivation and value. It’s also a strong gift idea for anyone starting a journey into programming, data science, or digital AI applications, offering a solid foundation that scales with ambition and curiosity.

Key Highlights:

• Clear, beginner-friendly introduction to Python tailored for CS and DS audiences
• Balanced emphasis on fundamentals and modern data-centric applications
• Real-world datasets and AI-focused projects to build market-relevant skills
• Interactive learning through included Jupyter Notebook supplements
• Progressive coverage from basics to object-oriented programming
• Practical guidance for data science workflows, visualization, and cloud contexts
• Course-ready structure that supports both classroom use and self-study
• Premium, durable paperback designed to be the go-to reference for new programmers

About the Author:
The Deitels—Paul J. Deitel and Harvey Deitel—are renowned computer science educators and prolific programming authors whose textbooks have shaped generations of learners. Known for their practical, example-driven approach, they have written widely used titles across languages and paradigms, consistently emphasising a strong foundation in theory paired with real-world coding. In this book, they translate their long-standing teaching philosophy into a Python-focused approach that bridges computer science fundamentals with data science applications, artificial intelligence contexts, and cloud-based projects. Their work is celebrated for clarity, structured progression, and projects that help readers see tangible results from their learning, making this title a trusted companion for students and instructors alike.

Why You’ll Love This Book:
If you’re aiming to build solid programming skills that translate into data analysis and AI-ready capabilities, this book delivers. The clear, paced instruction helps readers master Python while simultaneously exploring how code powers modern technologies in business, research, and industry. The integrated projects and real-world datasets provide motivation to keep turning pages, while the Jupyter Notebook supplements offer an immediate, hands-on experience. Whether you’re studying for a course, preparing for internships, or pursuing personal projects, this paperback acts as a reliable, long-term reference that grows with your knowledge and curiosity.

Please Note: The individual books included in this listing will be dispatched as per the original UK ISBN and UK edition cover image shown in the image.