This course introduces the fundamentals of LangChain, including LangChain Expression Language (LCEL) and building a basic chatbot program. From there, you'll learn to leverage LangChain’s prompt templates and utilize output parsers to generate high-quality, structured outputs from large language models.
Overview
Syllabus
- Welcome to the Course
- Get started with a course overview, and check out the technical requirements and how to get an OpenAI API key.
- Creating a Simple LangChain application
- Learn to build a simple LangChain app: integrate LLMs, manage chat history, use prompt templates, and apply few-shot prompting to create customizable chatbots with memory.
- Structured Outputs
- Discover structured outputs in AI: transform responses into actionable JSON for integration. Utilize schemas, parsers, and function calls to enhance reliability and automation in workflows.
- LangChain Structured Outputs
- Learn to parse and structure LLM outputs in LangChain using output parsers, TypedDict, Pydantic models, and automatic error correction for robust workflows.
- What’s Next
- Upgrade to the full Nanodegree program to keep learning and go further.
Taught by
Henrique Santana
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