LangChain Fundamentals Training in Copenhagen, Denmark

This course introduces participants to LangChain, a leading framework for developing applications powered by Large Language Models (LLMs). It covers the core building blocks, integrations, and use cases of LangChain, enabling learners to build conversational AI, intelligent agents, and workflow automation solutions. The program blends concepts, hands-on labs, and project-based learning.

Foundations of LangChain

Introduction to LangChain

• What is LangChain and why use it?

• LangChain ecosystem & components

• Installation and setup

Core Concepts

• Models (LLMs, ChatModels, Embeddings)

• Prompts and PromptTemplates

• Chains: Sequential, MapReduce, and Custom chains

Memory in LangChain

• ConversationBufferMemory, ConversationKGMemory, VectorStore-backed memory

Tools, Agents, and Applications

Working with Agents

• Introduction to agents and tools

• Toolkits (Python REPL, API calls, search)

Data Augmented Generation (RAG)

• Introduction to vector databases (FAISS, Pinecone, Chroma)

• Document loaders and text splitters

• RetrievalQA and ConversationalRetrievalChain

Deployment and Real-World Use Cases

• LangChain in production (streaming, async, scalability)

• Use cases: chatbots, research assistants, workflow automation

Hands-on Exercises

Summary and Conclusion