{"id":13475,"date":"2026-08-10T10:59:49","date_gmt":"2026-08-10T10:59:49","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-master-langchain-build-llm-apps-rag-pipelines-with-python-2025-10\/"},"modified":"2026-08-10T10:59:49","modified_gmt":"2026-08-10T10:59:49","slug":"udemy-master-langchain-build-llm-apps-rag-pipelines-with-python-2025-10","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-master-langchain-build-llm-apps-rag-pipelines-with-python-2025-10\/","title":{"rendered":"Udemy \u2013 Master LangChain: Build LLM Apps & RAG Pipelines with Python 2025-10"},"content":{"rendered":"
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Description<\/h2>\n

Master LangChain: Build LLM Apps & RAG Pipelines with Python is a course on using LangChain to build powerful AI applications published by Udemy Online Academy. This course teaches you how to build powerful AI applications using LangChain, guiding you from the basics to advanced, production-ready systems. You will learn how large language models interact with tools, memory, and external data, and how to design modular AI workflows using LangChain\u2019s core components. The course explains Retrieval Augmentative Generation (RAG) in a practical, step-by-step way\u2014including document loading, text splitting, embeddings, vector databases, and retrieval optimization\u2014then shows you how to build complete RAG pipelines for real-world use.<\/p>\n

This course covers LangChain basics, LLM integration, notification formats, tools and agents, memory systems, embeddings, text segmentation, vector stores, retrieval methods, RAG pipeline construction, optimization techniques, evaluation, deployment, and hands-on Python projects. With hands-on Python projects, you will build LLM-based chatbots, data assistants, automation tools, and custom applications, gaining the skills needed to efficiently develop, evaluate, and deploy modern AI systems.<\/p>\n

What you will learn in Master LangChain: Build LLM Apps & RAG Pipelines with Python:<\/h3>\n