Modularize with LangChain, Build Agents with LangGraph, and Monitor with LangSmith

What you'll learn
Master LCEL Orchestration: Build highly efficient, composable AI pipelines using the LangChain Expression Language and Runnable interfaces.
Develop Autonomous Agents: Use create_agent to build intelligent assistants that can reason and interact with external tools.
Architect Stateful Graphs: Design non-linear AI workflows using LangGraph to handle complex branching and looping logic.
Implement Robust Persistence: Use Checkpointers to save graph state, enabling agents to resume tasks and maintain memory.
Enable Production Monitoring: Set up LangSmith to trace every step of your application's execution for rapid debugging and optimization.
Evaluate AI Performance: Leverage LangSmith datasets and functions to monitor latency, cost, and output quality in real-world scenarios.

Requirements
Basic Python Knowledge: Familiarity with Python syntax, functions, and list comprehensions is required.
API Basics: A general understanding of how to use API keys (e.g., OpenAI or Anthropic) and make basic web requests.
Problem-Solving Mindset: No prior AI experience is needed, but a desire to build and iterate on complex systems is essential.

Description