{"id":7176,"date":"2026-08-10T09:41:23","date_gmt":"2026-08-10T09:41:23","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-gen-ai-llm-rag-two-in-one-langchain-llamaindex-2024-10\/"},"modified":"2026-08-10T09:41:23","modified_gmt":"2026-08-10T09:41:23","slug":"udemy-gen-ai-llm-rag-two-in-one-langchain-llamaindex-2024-10","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-gen-ai-llm-rag-two-in-one-langchain-llamaindex-2024-10\/","title":{"rendered":"Udemy \u2013 Gen AI \u2013 LLM RAG Two in One \u2013 LangChain + LlamaIndex 2024-10"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Gen AI Course \u2013 LLM RAG Two in One \u2013 LangChain + LlamaIndex. This course leverages the power of LangChain and LlamaIndex frameworks, along with OpenAI GPT and Google Gemini APIs, and vector databases such as ChromaDB and Pinecone. This course is designed to provide you with a comprehensive understanding of LLM RAG Advanced Application Development through in-depth conceptual learning and hands-on sessions. This course covers the essential aspects of LLM RAG applications and examines the components of both frameworks such as Agents, Tools, Chains, Memory, QueryPipelines, Retrievers and Query Engines in a clear and concise manner. Also, you will enter the world of linguistic embeddings and vector databases, allowing you to develop efficient semantic search and similarity-based RAG applications. Additionally, this course covers various prompt engineering techniques to increase the performance of your RAG applications. This dual approach gives you a broader view of RAG development and allows you to exploit the strengths of both LangChain and LlamaIndex in your projects.<\/span><\/p>\n

What you will learn in this course<\/span><\/h3>\n