This course covers the fundamentals and practical application of AI, including its history, core concepts, and future trends. Learners explore critical topics such as hallucinations, data provenance, security, trust, ethics, transparency, explainability, and model collapse. With hands-on exercises in API coding with ChatGPT, prompt engineering, and SES, along with dynamic prompt design and response decoding.
Distributed ledger technology, smart contracts, consensus mechanisms, and enterprise blockchain for healthcare. Based on the Springer textbook.
V-EGRCSbyD framework for responsible AI. Ethical principles, governance, regulatory compliance (EU AI Act, IEEE), and practical implementation.
AI and ML for threat detection, incident response, vulnerability assessment and security automation.