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Python-Powered Business Analytics: A Complete Guide to Data-Driven Decision Making
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- FormatePub
- ISBN8230662402
- EAN9798230662402
- Date de parution09/05/2025
- Protection num.pas de protection
- Infos supplémentairesepub
- ÉditeurIndependently Published
Résumé
Python-Powered Business Analytics: A Complete Guide to Data-Driven Decision Making is a comprehensive textbook designed for business students and professionals seeking to leverage Python programming for data analysis. Published in April 2025, this introductory guide assumes no prior programming experience, making it accessible for business, management, and finance students. The book takes a holistic approach, covering Python fundamentals alongside essential mathematical and statistical concepts, machine learning methods, and their practical business applications.
The text features a running case study to help readers apply theoretical knowledge to real-world scenarios. It includes practical examples demonstrating business analytics applications such as customer churn prediction, fraud detection, and sales forecasting. Each chapter contains learning objectives, practical exercises, and summaries to support the learning process. The book covers both supervised and unsupervised machine learning techniques, data visualization, and data manipulation using key libraries like Pandas, NumPy, and Matplotlib.
It emphasizes actionable insights and decision-making rather than just technical implementation, making it ideal for business professionals looking to enhance their analytical capabilities.
The text features a running case study to help readers apply theoretical knowledge to real-world scenarios. It includes practical examples demonstrating business analytics applications such as customer churn prediction, fraud detection, and sales forecasting. Each chapter contains learning objectives, practical exercises, and summaries to support the learning process. The book covers both supervised and unsupervised machine learning techniques, data visualization, and data manipulation using key libraries like Pandas, NumPy, and Matplotlib.
It emphasizes actionable insights and decision-making rather than just technical implementation, making it ideal for business professionals looking to enhance their analytical capabilities.
Python-Powered Business Analytics: A Complete Guide to Data-Driven Decision Making is a comprehensive textbook designed for business students and professionals seeking to leverage Python programming for data analysis. Published in April 2025, this introductory guide assumes no prior programming experience, making it accessible for business, management, and finance students. The book takes a holistic approach, covering Python fundamentals alongside essential mathematical and statistical concepts, machine learning methods, and their practical business applications.
The text features a running case study to help readers apply theoretical knowledge to real-world scenarios. It includes practical examples demonstrating business analytics applications such as customer churn prediction, fraud detection, and sales forecasting. Each chapter contains learning objectives, practical exercises, and summaries to support the learning process. The book covers both supervised and unsupervised machine learning techniques, data visualization, and data manipulation using key libraries like Pandas, NumPy, and Matplotlib.
It emphasizes actionable insights and decision-making rather than just technical implementation, making it ideal for business professionals looking to enhance their analytical capabilities.
The text features a running case study to help readers apply theoretical knowledge to real-world scenarios. It includes practical examples demonstrating business analytics applications such as customer churn prediction, fraud detection, and sales forecasting. Each chapter contains learning objectives, practical exercises, and summaries to support the learning process. The book covers both supervised and unsupervised machine learning techniques, data visualization, and data manipulation using key libraries like Pandas, NumPy, and Matplotlib.
It emphasizes actionable insights and decision-making rather than just technical implementation, making it ideal for business professionals looking to enhance their analytical capabilities.
