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A Beginner's Guide To DATA SCIENCE

About A Beginner's Guide To DATA SCIENCE

This book is designed for aspiring data scientists who want to start their careers in data science, even if they don't have coding skills. It provides a comprehensive introduction to the foundations of data science and its applications, using simple language that is easy for beginners to understand. No technical expertise is required to master the material in this book. It is an ideal resource for anyone looking to learn about data science in an accessible and straightforward way. Key features include: Introduction to data science History of data science Data science life-cycle Data science tools and technologies Data science methodology Data science models Developing data science business strategy Managing data science projects Becoming a data scientist, data engineer etc. Big data Data Mining Artificial intelligence Machine learning Deep learning Neural networks Mathematical analysis Statistical modelling Understanding the fundamentals of data science programming languages Database structures and principles Robotic Process Automation Data science acronyms You need to know And a lot more.

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  • Language:
  • English
  • ISBN:
  • 9781447826552
  • Binding:
  • Paperback
  • Pages:
  • 288
  • Published:
  • January 5, 2023
  • Dimensions:
  • 152x17x229 mm.
  • Weight:
  • 471 g.
Delivery: 1-2 weeks
Expected delivery: December 7, 2024

Description of A Beginner's Guide To DATA SCIENCE

This book is designed for aspiring data scientists who want to start their careers in data science, even if they don't have coding skills. It provides a comprehensive introduction to the foundations of data science and its applications, using simple language that is easy for beginners to understand. No technical expertise is required to master the material in this book. It is an ideal resource for anyone looking to learn about data science in an accessible and straightforward way.
Key features include:
Introduction to data science
History of data science
Data science life-cycle
Data science tools and technologies
Data science methodology
Data science models
Developing data science business strategy
Managing data science projects
Becoming a data scientist, data engineer etc.
Big data
Data Mining
Artificial intelligence
Machine learning
Deep learning
Neural networks
Mathematical analysis
Statistical modelling
Understanding the fundamentals of data science programming languages
Database structures and principles
Robotic Process Automation
Data science acronyms You need to know
And a lot more.

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