📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI for Fraud Detection: Basics, from foundations to a certified capstone project.
Outline
What is Fraud Detection? • Role of AI in Identifying Suspicious Activity • Traditional vs AI-Based Fraud Detection • Applications Across Finance, E-Commerce, and Insurance
Outline
Types of Fraud Data and Transaction Data • Patterns, Behaviors, and Red Flags • Normal vs Suspicious Activity • Importance of Data Quality and Privacy
Outline
Introduction to Anomaly Detection • Risk Scoring Concepts • Pattern Recognition in Transactions • Simple Idea of Alerts and Fraud Flags
Outline
AI in Banking Fraud Detection • AI in E-Commerce and Payment Security • Bias, Privacy, and False Alerts • Limitations of Fraud Detection Models
Outline
Emerging Trends in AI-Based Fraud Prevention • AI in Cybersecurity and Digital Trust • Career Opportunities in Fraud Analytics and Risk Management • Mini Learning Activity / Concept-Based Practice
Earn government-registered certification in AI for Fraud Detection: Basics
e-Certificate and e-Marksheet issued on successful completion.
