Business Analytics with Python: Essential Skills for Business Students
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.

1145200583
Business Analytics with Python: Essential Skills for Business Students
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.

59.0 In Stock
Business Analytics with Python: Essential Skills for Business Students

Business Analytics with Python: Essential Skills for Business Students

Business Analytics with Python: Essential Skills for Business Students

Business Analytics with Python: Essential Skills for Business Students

Paperback

$59.00 
  • SHIP THIS ITEM
    In stock. Ships in 1-2 days.
  • PICK UP IN STORE

    Your local store may have stock of this item.

Related collections and offers


Overview

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.


Product Details

ISBN-13: 9781398617179
Publisher: Kogan Page, Ltd.
Publication date: 03/25/2025
Pages: 408
Product dimensions: 6.69(w) x 9.45(h) x 0.00(d)

About the Author

Bowei Chen is an Associate Professor in Marketing Analytics and Data Science at the Adam Smith Business School, University of Glasgow, UK. He is the Programme Director of the MSc in Business Analytics.

Gerhard Kling is Professor in Finance at the University of Aberdeen, UK. He has worked in higher education (SOAS, University of Southampton, UWE, Utrecht University) and consulting (McKinsey).

Table of Contents

* Section - ONE: Introduction and preliminaries; ** Chapter - 01: Introduction; ** Chapter - 02: Mathematical foundations of business analytics; ** Chapter - 03: Getting started with python; ** Chapter - 04: Data wrangling; ** Chapter - 05: Data visualization; * Section - TWO: Methods and techniques; ** Chapter - 06: Linear regression; ** Chapter - 07: Logistic regression; ** Chapter - 08: Neural networks; ** Chapter - 09: K-nearest neighbours; ** Chapter - 10: Naïve bayes; ** Chapter - 11: Tree-based methods; ** Chapter - 12: Support vector machines; ** Chapter - 13: Principal component analysis; ** Chapter - 14: Cluster analysis; * Section - THREE: Applications and tools; ** Chapter - 15: Modelling supply chains – use cases; ** Chapter - 16: User interfaces and web applications; ** Chapter - 17: Answers to exercises;
From the B&N Reads Blog

Customer Reviews