Data science & Analytics using Python & R
- Author Gaurav Kumar, Amit Doegar, Gautam Pal
- ISBN: 9788199713628
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₹ 169.00
| Book Detail | |
| About The Author's | Gaurav Kumar has more than 24 years of experience in Teaching, Training, Research and Industry with delivery of sessions in over 700 workshops for academic institutions and government departments including NITTTR, NITs, Central Universities, MSME, DoPT, Defense Staff, Law Enforcement Agencies and many others. Dr. Amit Doegar was graduated in Computer Science & Engineering with distinction from Karnataka University, Dharwad in 1998 and an M.E. in Computer Science & Engineering from Panjab University, Chandigarh in 2008. He has completed his PhD in the area of Image Forensics from Panjab University, Chandigarh. Gautam Pal, Bachelor of Engineering (B.E.) in Computer Science & Engineering from Tripura Engineering College (Now NIT Agartala, India), M.Tech in Computer Science & Engineering from NIT Agartala. He is now pursuing PhD in Video Image Processing. Mr. Pal is now working as Associate Professor in the Department of Computer Science & Engineering, Tripura Institute of Technology, Agartala, Tripura, India. |
| What's special / Useful in this book | Key Features Dual-language approach: Learn analytics using both Python and R side by side Beginner-friendly yet advanced-ready: Starts from fundamentals and progresses to applied analytics Hands-on learning: Emphasis on coding, experimentation, and interpretation Academic and industry relevance: Suitable for coursework, training programs, and professional upskilling Tool-agnostic thinking: Focus on analytical reasoning beyond syntax Who Should Read This Book Undergraduate and postgraduate students in Data Science, Computer Science, Statistics, Management, and Engineering Faculty members and trainers teaching analytics-related subjects Working professionals transitioning into data science roles Researchers seeking applied analytical techniques Self-learners aiming for a structured and practical learning path |
| Publication Year | 2026 |
| Edition | First Edition |
| Pages | 152 |
| Preface | |
| Preface | In today’s data-driven world, the ability to extract meaningful insights from vast and complex datasets has become one of the most valuable skills across industries. The fields of Data Science and Analytics have rapidly evolved into essential disciplines, enabling data-informed decision-making, predictive modeling, and strategic innovation. This book, Data Science and Analytics using Python and R, is designed to serve as a comprehensive and practical guide for learners, educators, and professionals who aspire to explore the power of data through two of the most popular programming languages—Python and R. Python and R each have unique strengths in data handling, visualization, and statistical analysis. While Python offers flexibility, scalability, and integration with modern machine learning frameworks, R remains a powerful tool for statistical modeling, visualization, and research-oriented analytics. This book bridges both worlds—showcasing how to approach problems from multiple perspectives, thereby empowering readers to choose the best tools for their analytical goals. |
| Table of Contents | |
| Table of Contents | 1. Introduction to Data Science and Analytics 2. Data, Tools and Ecosystems 3. Data Wrangling and Preprocessing 4. Exploratory Data Analysis (EDA) 5. Time Series and Streaming Data Analytics 6. Introduction to Machine Learning 7. Machine Learning Models – Regression, Classification and Clustering 8. Advanced and Specialized Models – Optimization, Neural Networks and Model Interpretation 9. Text Analysis, Visualization and Emerging Trends 10. Generative AI and Large Language Models |