Business Analytics with Python : Essential Skills for Business Students

Bowei Chen

ISBN 10: 1398617172 / ISBN 13: 9781398617179

Published by Kogan Page, Kogan Page, 2025

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Data-driven decision-making is a fundamental component of business success. Use this textbook to learn the core knowledge and techniques for analyzing business data with Python programming.Business Analytics with Python assumes no prior knowledge or experience in computer science, presenting the technical aspects of the subject in an accessible, introductory way for students on business courses. It features chapters on linear regression, neural networks and cluster analysis, with a running case study that enables students to apply their knowledge. Students will also benefit from real-life examples to show how business analysis has been used for such tasks as customer churn prediction, credit card fraud detection and sales forecasting. This book presents a holistic approach to business analytics: in addition to Python, it covers mathematical and statistical concepts, essential machine learning methods and their applications. Business Analytics with Python comes complete with practical exercises and activities, learning objectives and chapter summaries as well as self-test quizzes. It is supported by online resources that include lecturer PowerPoint slides, study guides, sample code and datasets and interactive worksheets. This textbook is ideal for students taking upper level undergraduate and postgraduate modules on analytics as part of their business, management or finance degrees.

Seller Inventory # 9781398617179

Bibliographic Details

• Title: Business Analytics with Python : Essential Skills for Business Students
• Publisher: Kogan Page, Kogan Page
• Publication Date: 2025
• Language: English
• ISBN 10: 1398617172
• ISBN 13: 9781398617179
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 244W x 170H x 22D millimeters 244 millimeters width by 170 millimeters height by 22 millimeters depth
• Weight: 705 grams

About this title

Synopsis

Your essential textbook for mastering business analytics through Python.

Business Analytics with Python by Bowei Chen and Gerhard Kling is the definitive guide for upper-level undergraduate and postgraduate students studying business, management or finance. Designed to support analytics modules that prioritize practical application, this textbook introduces students to data-driven decision-making through Python, without assuming a background in computer science. It aligns with course outcomes by integrating statistical, mathematical and machine learning techniques into a unified business context.

This textbook takes a holistic approach to business analytics, exploring how Python can be used to interpret and solve real-world problems. From foundational coding skills to the implementation of supervised and unsupervised machine learning methods, students learn how to translate data into insight across key business functions. Through industry-relevant case studies, including customer churn analysis, fraud detection and sales forecasting, learners build confidence in applying analytics to real organizational challenges.

Pedagogical features include:
- A running case study that reinforces practical learning across chapters
- Clear learning objectives and chapter summaries to track progress
- Step-by-step exercises and coding activities to build analytical fluency
- Examples grounded in real business applications for immediate relevance

Whether preparing for exams or building analytical capability for a future career, this textbook equips students with the tools to turn business data into strategic advantage.

About the Authors

Bowei Chen is an Associate Professor of Marketing Analytics and Data Science at the Adam Smith Business School, University of Glasgow. He is also the Programme Director of the MSc in Finance and Management and an ESRC IAA Reviewer.

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.