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Foundations of Programming, Statistics, and Machine Learning for Business Analytics

Foundations of Programming, Statistics, and Machine Learning for Business Analytics

Hardback

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  • Release Date: 28/04/2023
  • Barcode: 9781529620900
  • Genre: Business & Finance
  • Imprint: Sage
  • Publisher: Sage Publications
Foundations of Programming, Statistics, and Machine Learning for Business Analytics

Foundations of Programming, Statistics, and Machine Learning for Business Analytics

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DESCRIPTION

This book provides an introduction to the key concepts in programming, statistics and machine learning needed by business analytics students, assuming no prior knowledge and taking a step-by-step approach to help students build up their confidence.


Business Analysts and Data Scientists are in huge demand, as global companies seek to digitally transform themselves and leverage their data resources to realize competitive advantage.

This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics. 

Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice.

Key features:

·       Introduces programming fundamentals using R and Python

·       Covers data structures, data management and manipulation and data visualization

·       Includes interactive coding notebooks so that you can build up your programming skills progressively

Suitable as an essential text for undergraduate and postgraduate students studying Business Analytics or as pre-reading for students studying Data Science.

Ram Gopal is Pro-Dean and Professor of Information Systems at the University of Warwick.

Daniel Philps is an Artificial Intelligence Researcher and Head of Rothko Investment Strategies.

Tillman Weyde is Senior Lecturer at City, University of London.



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