CourseGenix

Explore

Generative AI (Langchain, Langgraph, Langsmith, Pydantic AI)

4 Units16 Lessons
Unit 1

langsmith

Introduction to Langsmith for AI Tracing
Key Features of Langsmith for Evaluation
Real-World Project: Implementing Langsmith in AI Workflow Monitoring
Advanced Langsmith Techniques for AI Optimization
Unit 2

langchain

Basics of Langchain Framework
Building Simple Chains with Langchain
Integrating Prompts and Models in Langchain
Real-World Project: Developing a Chatbot with Langchain
Enhancing Langchain Chains for Complex AI Tasks
Unit 3

pydantic AI

Fundamentals of Pydantic in AI Data Modeling
Advanced Data Schemas with Pydantic for AI
Real-World Project: Applying Pydantic in AI Data Pipelines
Optimizing Pydantic Models for Generative AI Outputs
Unit 4

langgraph

Introduction to Langgraph Workflows
Real-World Project: Building a Multi-Agent System with Langgraph
Advanced Graph Structures in Langgraph
Unit 1•Chapter 4

Advanced Langsmith Techniques for AI Optimization

Summary

User instructs to create a summary under 250 words, focusing solely on the core content, excluding any mentions of sponsors or off-topic elements, and avoiding any introductory phrases.

Concept Check

0/5

What is LangSmith's primary role in AI optimization?

How does LangSmith enhance prompt engineering?

In LangSmith, what optimizes AI workflows?

What technique in LangSmith improves model accuracy?

How does LangSmith handle AI performance issues?

PreviousReal-World Project: Implementing Langsmith in AI Workflow Monitoring