Prerequisites: Strong Python programming skills, solid understanding of Large Language Models (LLMs), and prior experience with basic LangChain concepts.

Level: Advanced

What You'll Learn

• Advanced Architecture

  Design and implement complex, multi-step chains and agents using advanced LangChain features.

• Memory Management

  Select and configure appropriate memory mechanisms for maintaining long-term conversational context.

• Data Retrieval Optimization

  Architect and optimize retrieval-augmented generation (RAG) pipelines for production scale.

• Evaluation and Monitoring

  Implement comprehensive evaluation, monitoring, and observability for LangChain applications using tools like LangSmith.

• Optimization and Scaling

  Apply performance optimization techniques and cost management strategies for LLM applications.

• Deployment Strategies

  Package, deploy, and scale LangChain applications using containerization and cloud-native technologies.

• Security Implementation

  Integrate security best practices throughout the LangChain application lifecycle.