Course
Developing LLM Applications with LangChain
Intermediate
Updated 05/2025Start Course for Free
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PythonArtificial Intelligence3 hours10 videos33 Exercises2,750 XP20,829Statement of Accomplishment
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Course Description
Foundation for Developing in the LangChain Ecosystem
Augment your LLM toolkit with LangChain's ecosystem, enabling seamless integration with OpenAI and Hugging Face models. Discover an open-source framework that optimizes real-world applications and allows you to create sophisticated information retrieval systems unique to your use case.Chatbot Creation Methodologies using LangChain
Utilize LangChain tools to develop chatbots, comparing nuances between HuggingFace's open-source models and OpenAI's closed-source models. Utilize prompt templates for intricate conversations, laying the groundwork for advanced chatbot development.Data Handling and Retrieval Augmentation Generation (RAG) using LangChain
Master tokenization and vector databases for optimized data retrieval, enriching chatbot interactions with a wealth of external information. Utilize RAG memory functions to optimize diverse use cases.Advanced Chain, Tool and Agent Integrations
Utilize the power of chains, tools, agents, APIs, and intelligent decision-making to handle full end-to-end use cases and advanced LLM output handling.Debugging and Performance Metrics
Finally, become proficient in debugging, optimization, and performance evaluation, ensuring your chatbots are developed for error handling. Add layers of transparency for troubleshooting.Prerequisites
Introduction to Embeddings with the OpenAI APIChatGPT Prompt Engineering for Developers1
Introduction to LangChain & Chatbot Mechanics
2
Chains and Agents
3
Retrieval Augmented Generation (RAG)
Developing LLM Applications with LangChain
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