📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Fraudsheild AI Lab Course, from foundations to a certified capstone project.
Outline
Explore common fraud types including identity theft, payment fraud, and money‑laundering. • Identify digital transaction and API vulnerabilities within modern banking systems. • Trace the evolution from rule‑based detection to AI‑driven solutions.
Outline
Understand supervised vs. unsupervised learning and key algorithms. • Apply AI to real‑time transaction monitoring using behavioral biometrics. • Review case studies such as JPMorgan’s credit‑card fraud reduction.
Outline
Implement autoencoders, isolation forests, and graph‑based models. • Leverage NLP for anti‑money‑laundering sentiment analysis. • Integrate blockchain and federated learning for secure data sharing.
Outline
Deploy models via APIs and cloud services such as AWS Fraud Detector. • Mitigate bias, manage false positives, and ensure regulatory compliance. • Adopt best practices for data privacy, model auditing, and scaling.
Outline
Explore quantum‑resistant AI and generative‑AI fraud simulation. • Assess AI’s role in DeFi, cross‑border fraud prevention, and zero‑trust architectures. • Identify career pathways and ongoing research opportunities.
Earn government-registered certification in Fraudsheild AI Lab Course
e-Certificate and e-Marksheet issued on successful completion.
