LangChain Unleashed: Building Decentralized Language Applications for the Future

Overview

🕮 Off the shelf (OTS)

This course is designed for software developers, data scientists, ML engineers, and technical professionals who want to build applications that integrate large language models (LLMs) using the LangChain framework. It is suitable for those working on natural language interfaces, automation tools, or advanced AI systems.

Participants should have a working knowledge of Python. Familiarity with APIs and basic concepts of machine learning or large language models is recommended.

The LangChain Training Course provides an in-depth introduction to developing LLM-powered applications using LangChain. Participants will learn the LangChain architecture and core components, how to manage memory and chains, how to integrate external tools and APIs, and how to implement agents for dynamic task execution. The course also covers retrieval-augmented generation (RAG) and deployment strategies for production-ready applications.

Key Topics Covered:
• Overview of LangChain and its architecture
• Prompt templates, chains, and memory management
• Integration with external tools, APIs, and agents
• Retrieval-augmented generation (RAG) using vector stores
• Evaluation, debugging, and monitoring of LLM applications
• Deployment strategies and best practices

The course is delivered over three days and includes hands-on exercises to reinforce learning.