Certified Generative AI Architect with Knowledge Graphs

About this course

The Certified Generative AI Architect with Knowledge Graphs program is a comprehensive, advanced-level certification designed to equip professionals with the tools, frameworks, and hands-on experience to architect cutting-edge Generative AI (GenAI) systems that are intelligent, explainable, and scalable. This course combines the power of Large Language Models (LLMs), Knowledge Graphs, Retrieval-Augmented Generation (RAG), and agent-based orchestration to help you build production-grade AI solutions that go beyond simple prompt engineering.

You’ll begin by mastering the foundations of GenAI architecture, including the capabilities of modern LLMs, the rise of agentic AI systems, and how memory, context, and reasoning enhance performance. You'll explore the anatomy of RAG pipelines, dive into context-aware generation, and set the stage for knowledge-enhanced AI applications.

From there, we’ll delve deep into semantic technologies. You’ll learn to design and build ontologies using tools like Protégé and TopBraid Composer, construct and query graph databases using RDF, OWL, SPARQL, and Cypher, and manage the lifecycle of enterprise-grade knowledge systems. This enables you to drive semantic search, entity disambiguation, and structured reasoning in real-world deployments.

The course also covers how to build hybrid retrieval systems by integrating vector databases like FAISS, Weaviate, and Pinecone with graph-based reasoning. You'll implement advanced RAG pipelines that combine semantic filtering, graph traversal, and vector simila

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