Certified Generative AI Architect with Knowledge Graphs
Design and Deploy Scalable GenAI Systems with Ontologies, RAG, and Multi-Agent Architectures
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Certified Generative AI Architect with Knowledge Graphs is a Development course on Udemy. Design and Deploy Scalable GenAI Systems with Ontologies, RAG, and Multi-Agent Architectures The material is organised so learners can progress from the fundamentals to applying what they have learned in realistic scenarios.
Key Skills You Will Learn
- Design end-to-end Generative AI architectures that combine LLMs, retrieval-augmented generation (RAG), agent workflows, and knowledge graphs.
- Model and implement ontologies and semantic knowledge graphs using tools like Protégé, RDF/OWL standards, and graph databases such as Neo4j or Stardog.
- Build hybrid retrieval systems that integrate vector search (FAISS, Pinecone, Weaviate) with graph-based semantic querying for enhanced context and relevance.
- Develop multi-agent GenAI applications using LangGraph, AutoGen, or CrewAI, enabling memory-aware, tool-using, and role-based intelligent agents.
- Deploy and scale GenAI systems in cloud-native environments using Docker, Kubernetes, AWS Fargate, and Azure Container Apps with observability and monitoring.
- Translate business problems into knowledge-driven AI solutions and deliver stakeholder-ready architecture, documentation, and ROI narratives.
Who This Course Is For
This course suits learners who want a guided, self-paced path into Development, from complete beginners to practitioners looking to refresh or formalise their knowledge. Check the curriculum and requirements section on Udemy to confirm it matches your current level.
Our Take
If the topic aligns with your goals, this is a convenient way to build skills on your own schedule. Udemy courses include lifetime access to the enrolled content, so you can revisit lessons whenever you need them.
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