Data Science with Python for Indian Students

Data Science with Python for Indian Students takes you from Python basics to working with real datasets — cleaning, analysing, visualising and building your first machine learning models. Written in simple language for Indian college students and career starters, with every concept backed by fully worked examples you can run yourself.

Why Choose This Data Science Book?

• Written for Indian students — matched to B.Tech CSE, AI & Data Science, BCA and MCA syllabi, with datasets and examples from contexts you recognise
• Every program tested and runnable — code executes exactly as printed, and the output in the book is the real output you'll see
• Practice with solutions included — questions first, answers after, so you can self-test honestly before checking
• Complete path, no gaps — Python foundations through NumPy, Pandas, visualisation, statistics and machine learning in one book

Who Is This Data Science Book For?

• B.Tech / B.E. students in Computer Science, IT, AI & Data Science and allied branches
• BCA, MCA, BSc Computer Science, BSc Statistics and Diploma students
• Beginners starting data science with no prior programming background
• Working professionals switching into data analyst and data science roles
• Students preparing for placements, internships and data science interviews

What You Will Learn

• Python for Data Science — the syntax, data types and logic you actually need, taught from scratch
• NumPy — arrays, indexing, broadcasting and numerical operations
• Pandas — Series and DataFrames, loading CSV and Excel files, filtering, grouping and merging
• Data Cleaning — handling missing values, duplicates, outliers and inconsistent data
• Data Visualisation — Matplotlib and Seaborn charts that communicate findings clearly
• Statistics for Data Science — mean, median, variance, distributions, correlation and hypothesis testing
• Exploratory Data Analysis — a repeatable method for making sense of any new dataset
• Machine Learning Basics — regression, classification, clustering and model evaluation with scikit-learn
• Practice Projects — end-to-end analyses that take a raw dataset through to conclusions

Book Details