This course offers valuable knowledge and skills to combat fraud within organizations. It is estimated that a typical organization loses approximately 5% of its annual revenue to fraudulent activities. By leveraging data, you will learn effective strategies to detect and prevent fraud. Throughout the course, you will gain expertise in utilizing supervised learning algorithms to identify fraudulent behavior based on historical patterns. Additionally, you will explore unsupervised learning methods to uncover new types of fraudulent activities. One of the challenges in fraud analytics is dealing with highly imbalanced datasets, particularly when classifying fraud versus non-fraud cases. This course equips you with techniques to effectively address this issue. The curriculum encompasses a blend of technical and theoretical insights, enabling you to practically implement fraud detection models. You will receive hands-on guidance on implementing these models, ensuring a comprehensive understanding of the subject matter. Furthermore, the course offers invaluable tips and advice derived from real-life experiences, helping you avoid common mistakes in fraud analytics. By the end of this course, you will possess the necessary skills and knowledge to effectively combat fraud and safeguard your organization's financial well-being.