Description

About The Book

This book serves as a comprehensive guide to learning data science through Python, combining theoretical foundations with practical coding examples. It is structured to take readers from the basics of Python programming to advanced data science applications, making it suitable for students, educators, and professionals.

The content begins with the foundations of data science and Python programming, explaining core concepts like predictive modeling, customer segmentation, fraud detection, and personalized recommendations. It also introduces various data types such as text, numeric, categorical, image, audio, video, geospatial, and time-series data.

Subsequent chapters cover methods of data collection and generation, including surveys, experiments, observational studies, web scraping, and sensor-based data gathering. Readers are guided through Python-based implementations for acquiring and simulating datasets.

A significant portion of the book is devoted to data visualization techniques, exploring charts, histograms, scatter plots, heatmaps, treemaps, word clouds, 3D visualizations, and more. Each visualization type is explained with Python code and outputs, enabling learners to understand both theory and application.

The book also emphasizes data manipulation, preprocessing, and cleaning using pandas, covering tasks such as handling missing values, outliers, encoding categorical variables, and ensuring consistency. Exploratory Data Analysis (EDA) is explored in detail, introducing descriptive statistics, measures of central tendency, dispersion, and position with step-by-step Python examples.

Later chapters introduce statistical modeling concepts integrated with programming techniques, and the text concludes with case studies and data science relationships, demonstrating practical applications across industries.

Overall, this book blends statistical theory, computational methods, and applied Python programming, making it a valuable resource for mastering data science concepts and applying them to real-world problems.

About The Author

Dr. Krishna Kumar P R, B.E (CSE), M.E (CSE), Ph.D (CSE), D.Lit. (CS & Social Service), is currently Professor and Head of the Department of Computer Science and Engineering at SEA College of Engineering & Technology, Bangalore-49 . With over 24+ years of experience in Teaching, Research, and Academic Administration, He is a recognized expert in IoT, Smart Cities, AI, Big Data, and Cybersecurity. He is the first author of the book “Blockchain Enabled Secure Big Data Computing for Smart Cities Using IoT” (Cipher Publisher, 2024, ISBN: 978-81-980505-2-6). Dr. Kumar has published over 85 research articles in reputed journals and conferences, holds multiple patents, and has led funded research projects worth over ₹3.9 crores from agencies like ICSSR, BIRAC, and DST. His contributions to education have earned him prestigious Honors, including the Karnataka Vibhushan Rathna Award (2025) and Bhisma Acharya Award (2024). He is a member of IEEE, ISTE, IEI, and CSI, and actively serves as a reviewer and editor for reputed journals and conferences Dr. Manjunath K V is an accomplished academician and researcher in the field of Computer Science and Engineering, with over 17 years of teaching experience and more than five years of active research engagement. Currently serving as an Associate Professor at Presidency University, Bangalore, he has also been a guest faculty member at BITS Pilani, Bangalore Centre, contributing to industry training programs. Dr. Manjunath KV holds a Ph.D. in Computer Science and Engineering, with his research interests spanning Data Science, Artificial Intelligence, Machine Learning, and Big Data Analytics. His work emphasizes real-world applications of data-driven techniques in domains such as finance, healthcare, and cybersecurity. He has published numerous research papers in reputed international journals and conferences, including contributions on predictive analytics, AI-based stock market forecasting, and intelligent data mining. He is the inventor of three patents centred on AI-enhanced data systems for secure data processing, real-time analytics, and intelligent decision-making frameworks. Throughout his career, he has taken up key academic and administrative responsibilities, including roles as IQAC Coordinator, Academic Coordinator, and Admission Coordinator. Dr. Manjunath has also organized and participated in several faculty development programs and workshops on emerging technologies, including IoT, Machine Learning, and Cloud Computing. With a passion for teaching and curriculum development, he has taught a wide range of undergraduate and postgraduate courses, particularly in areas like Cryptography, Network Security, Microcontrollers, and Software Architecture. His deep commitment to quality education, research, and academic excellence continues to inspire students and faculty alike in the field of Cyber Security and beyond. Mrs. Sowmya Rani is a dedicated academician and emerging researcher in the field of Computer Science and Engineering, with over 5 years of teaching experience. She is currently serving as an Assistant Professor in Department of CSE at SEA College of Engineering and Technology, Bangalore. She has actively involved in mentoring students and contributing to academic excellence. Her interests lie in the areas of Data Science, Machine Learning, and Artificial Intelligence. She is committed to continuous learning and has participated in several faculty development programs and workshops aimed at bridging the gap between academia and industry. Ms. Hithaishi KV, Mtech qualified expert in Computer science and Engineering is currently working as Assistant Professor in the CSE Department at SEA College of Engineering and technology Bangalore with 3 years of dedicated teaching for undergraduate students. She has been participated in various workshops, conferences and faculty development programs. She specializes in software development and programming languages. Her area of interest is Data science, cloud computing and IOT