The Data Science for Fraud Detection and Resolution course is a 15-hour program spread over three days. It aims to provide participants with practical skills to help their organizations apply data science techniques for fraud detection and identify instances of fraud. The course emphasizes the importance of using data models and analysis to identify symptoms of financial waste and build financial resilience and integrity within the organization.

Course Objectives: During this course, participants will gain the following skills and knowledge:

1. Practical Skills for Fraud Detection: Acquire practical skills to detect and resolve fraud by utilizing data science techniques.
2. Designing Data Models: Learn how to design effective data models for fraud detection, combining data analysis and proven methodologies.
3. Utilizing Data and Methodologies: Understand how to leverage data combined with proven methodologies to identify fraudulent activities targeting the organization, including fraud perpetrated by suppliers, customers, agents, middlemen, hackers, criminals, and internal personnel.
4. Early Fraud Detection: Gain insights into building early fraud detection models to identify and prevent fraudulent activities at an early stage.
5. Supporting Fraud Investigations: Learn how to support fraud investigations by utilizing data science approaches to provide evidence and insights for uncovering fraudulent activities.

The ultimate goal of this course is to empower participants to save costs by implementing data models and utilizing data to identify and address financial waste caused by fraudulent activities. By applying data science techniques and methodologies, participants will develop the skills needed to build true financial resilience and integrity within their organizations.

Note: The specific content and duration of the course may vary based on the actual program structure and the training provider offering the course.