Fundamentals of Data Science (Paperback)

Sanjeev J. Wagh

ISBN 10: 103207986X / ISBN 13: 9781032079868

Published by Taylor & Francis Ltd, 2025

About this Item

Paperback. Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science.Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processesReaders will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue.This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge.Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals. Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781032079868

Bibliographic Details

• Title: Fundamentals of Data Science (Paperback)
• Publisher: Taylor & Francis Ltd
• Publication Date: 2025
• Language: English
• ISBN 10: 103207986X
• ISBN 13: 9781032079868
• Binding: Paperback
• Condition: new

About this title

Synopsis

Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science.

Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes

Readers will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue.

This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge.

Features :

• Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets.
• Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools.
• Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice.
• Information is presented in an accessible way for students, researchers and academicians and professionals.

About the Author

Sanjeev J. Wagh, Manisha S. Bhende, Anuradha D. Thakare