Business Analytics with Python: Essential Skills for Business Students
Author: Bowei Chen (Author), Gerhard Kling (Author)
Publisher finelybook 出版社: Kogan Page
Publication Date 出版日期: 2025-03-25
Edition 版次: 1st
Language 语言: English
Print length 页数: 408 pages
ISBN-10: 1398617288
ISBN-13: 9781398617285
Book Description
Data-driven decision-making is a fundamental component of business success. Use this textbook to help you learn and understand the core knowledge and techniques needed for analysing business data with Python programming.
Business Analytics with Python is ideal for students taking upper level undergraduate and postgraduate modules on analytics as part of their business, management or finance degrees. It assumes no prior knowledge or experience in computer science, instead presenting the technical aspects of the subject in an accessible, introductory way for students. This book takes a holistic approach to business analytics, covering not only Python as well as mathematical and statistical concepts, essential machine learning methods and their applications.
Features include:
– Chapters covering preliminaries, as well as supervised and unsupervised machine learning techniques
– A running case study to help students apply their knowledge in practice.
– Real-life examples demonstrating the use of business analytics for tasks such as customer churn prediction, credit card fraud detection, and sales forecasting.
– Practical exercises and activities, learning objectives, and chapter summaries to support learning.
Review
“Business Analytics with Python stands out as a rare resource that successfully bridges the gap between theoretical concepts and real-world applications-something few tools manage to accomplish today. Its step-by-step approach and meticulously crafted examples ensure that readers don’t just learn about business analytics in the abstract, but actually gain the skills to apply these methods and techniques in practice. The hands-on guidance throughout makes advanced data analysis accessible, even to those without a strong quantitative background. In an era where actionable analytics skills are increasingly essential, this book serves as both a solid educational foundation and a practical reference, empowering students and professionals alike to confidently solve complex business problems with Python.” ― Nedko Krastev, Founder and CEO, 365 Data Science
“This book is a clear and practical blueprint for incorporating machine learning insights into business operational decisions. Drawing on my experience in operations management and business analytics, I appreciate how the authors seamlessly blend fundamental Python skills, advanced modelling techniques, and actionable business strategies. Their guidance empowers readers to streamline processes, improve efficiency, and translate predictive insights into tangible, real-world results. This is a great resource for anyone serious about leveraging machine learning to drive smarter, more impactful data-driven decisions.” ― Yufei Huang, Associate Professor in Operations Management, Trinity Business School, Trinity College Dublin
“This is a must-read for professionals and students looking to harness the power of Python in solving real-world business challenges. The book masterfully bridges the gap between programming fundamentals and practical applications in business analytics, providing readers with step-by-step guidance and hands-on examples. With its clear explanations, accessible approach, and industry-relevant use cases, this book empowers readers to confidently use Python to derive insights, make data-driven decisions and drive strategic outcomes. Whether you’re a beginner or looking to enhance your existing skills, this is an invaluable resource for staying competitive in today’s data-driven world.” ― Wei Zhou, Professor of Information & Operations Management, ESCP Business School
“In the FinTech industry, data fuels innovation and informed decision-making. This book equips students and professionals with the essential tools to analyze financial and business data, optimize operations, and uncover actionable insights through predictive analytics. It is an invaluable resource for those striving to excel in this fast-paced and highly competitive field.” ― Yu Zheng, Associate Professor of Fintech, Southwestern University of Finance and Economics, China, and CEO of Inboc Technologie.
About the Author
Gerhard Kling is a Professor in Finance at the University of Aberdeen. He has worked in higher education for over 18 years (SOAS, University of Southampton, UWE, Utrecht University). His current interests focus on machine learning (ML), artificial intelligence (AI), and their applications in FinTech and Green Finance.
