Description:

Data Science can feel overwhelming—complex mathematics, unfamiliar programming languages, and advanced algorithms often discourage beginners before they even begin. 'Data Science for Beginners' is written to change exactly that experience.

This book assumes no prior knowledge of mathematics, programming, or artificial intelligence. It starts from the absolute basics and gradually builds your understanding, step-by-step, until you are confident applying Data Science techniques to real-world problems.

This book walks you through the complete Data Science lifecycle—from understanding data and cleaning it, to building machine learning models, exploring deep learning, NLP, time series analysis, and responsible AI. Mathematical foundations such as probability and statistics are explained in a simple, intuitive manner, without unnecessary complexity. Every major concept is paired with hands-on Python examples, helping you see how theory actually works in practice. The book is perfect for average-level students and non-engineering learners.

What truly sets this book apart is its all-in-one approach. Instead of referring to multiple textbooks for math, programming, and Data Science concepts, everything you need is brought together in a single, well-structured volume. Real-life cases and industry-inspired examples help readers understand where and why these techniques are used.

Concise, practical, and easy to follow, the book serves both as a reliable academic textbook and a practical handbook—empowering students from any academic background to learn Data Science with confidence and clarity.

KEY FEATURES

• Build Foundational Learning: Starts from zero—no math, coding, or AI background needed.

• Syllabus Aligned: Precisely aligned with the syllabus following a clear, step-by-step learning flow.

• Job-Ready Skills: Developed by authors with combined academic and industry experience, every concept is reinforced through practical Python coding aligned with real-world problem-solving.

• All-in-One: From mathematics to machine learning, deep learning, NLP, time series, visualization, and ethical AI—all in a single, practical handbook.

TARGET AUDIENCE

• B.Tech. Computer Science Engineering & IT

• B.Tech. Data Science

• B.Sc./M.Sc. Data Science

• BCA/MCA