Is your data strategy ready for the future of AI?
LLMs, RAG, and agentic AI demand more than just data—they require structure, governance, and clarity. Without a robust framework, even the most advanced models risk generating flawed or biased outputs. This course explores how foundational data principles enable scalable, trustworthy generative AI solutions. You’ll examine how structured and unstructured data power today’s AI applications, and how frameworks can overcome common LLM limitations like hallucinations and outdated context. From analyzing LLM limitations to exploring RAG and agentic AI, each module highlights the critical role of data governance. Through case studies and expert-led discussions, you’ll gain practical skills in designing taxonomies and implementing enterprise-ready data foundations. By the end, you’ll be equipped to build AI systems that deliver consistent, ethical, and high-performing results.
