Deep Learning A-Z 2026: Mạng Nơ-ron, AI & Giải thưởng ChatGPT
Kirill Eremenko
Generative AI with Context: RAG, CAG & KAG Applications
Artificial intelligence is evolving fast, and the next frontier is context. Models that can understand, retrieve, and reason with the right information at the right time are not only more accurate - they’re smarter, more reliable, and closer to human‑like intelligence. This course, Context‑Aware AI, is designed to give you the skills and confidence to build those systems yourself.
Instead of just theory, you’ll get a guided journey through the most important context‑aware workflows: Retrieval Augmented Generation (RAG), Cache Augmented Generation (CAG), and Knowledge Augmented Generation (KAG). Each concept is introduced clearly, then reinforced with hands‑on projects that let you see the power of context in action. You’ll learn how to connect models to external knowledge, optimize performance with caching, and integrate knowledge graphs for structured reasoning.
What makes this course different is its balance of clarity and practicality. Complex ideas are broken down into intuitive explanations, supported by exercises and real‑world examples. By the end, you won’t just understand how context‑aware AI works - you’ll have built working pipelines that you can adapt to your own projects, whether you’re developing smarter chatbots, enterprise search tools, or advanced reasoning systems.
If you’re ready to move beyond generic AI responses and start creating applications that truly understand context, this course is your launchpad. Join us and take the next step toward building intelligent systems that think deeper, respond smarter, and deliver real value.
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