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Building Agents: Free Course

We just released a course with > 20 videos & notebooks focused on building agents. All code is open-source and the course is free!

Context
Back in June, I gave at talk at @aiDotEngineer on building agents with LangGraph. I got ~2 hrs of questions. We took these questions along with lots of feedback we've heard from users and built a course!

Module 1: Foundations
The first module includes several notebooks & videos that focus on what is an agent explained in simple terms, how to build various types of agents (routers, ReAct, etc), how to debug them w LangGraph Studio, and how to deploy them w LangGraph Cloud.

Module 2: Memory
One of the biggest questions we've heard is how to build long-running agents, which can remember important details. We show how memory works with LangGraph, and how to use various databases (SQLite, Postgres) to serve as agent memory.

Module 3: Human-In-The-Loop
Another central question with agents is allowing humans to approve actions (tools use) or modify the agent state (add feedback). We show various human in the loop interaction patterns that are supported in LangGraph, and also show how to stream the graph state during agent execution for human review.

Module 4: Controllability
The final module focuses on various design patterns for agent control flow, including parallelization of tasks and creating multi-agent teams with their own tasks / internal memory. This builds up into a customizable multi agent system for research that pulls together themes from the entire course.

Course (links to code, all videos):
https://academy.langchain.com/courses/intro-to-langgraph

http://www.tgoop.com/codeprogrammer 🔒

💡 #deeplearning #AI #ML #python
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Building Agents: Free Course

We just released a course with > 20 videos & notebooks focused on building agents. All code is open-source and the course is free!

Context
Back in June, I gave at talk at @aiDotEngineer on building agents with LangGraph. I got ~2 hrs of questions. We took these questions along with lots of feedback we've heard from users and built a course!

Module 1: Foundations
The first module includes several notebooks & videos that focus on what is an agent explained in simple terms, how to build various types of agents (routers, ReAct, etc), how to debug them w LangGraph Studio, and how to deploy them w LangGraph Cloud.

Module 2: Memory
One of the biggest questions we've heard is how to build long-running agents, which can remember important details. We show how memory works with LangGraph, and how to use various databases (SQLite, Postgres) to serve as agent memory.

Module 3: Human-In-The-Loop
Another central question with agents is allowing humans to approve actions (tools use) or modify the agent state (add feedback). We show various human in the loop interaction patterns that are supported in LangGraph, and also show how to stream the graph state during agent execution for human review.

Module 4: Controllability
The final module focuses on various design patterns for agent control flow, including parallelization of tasks and creating multi-agent teams with their own tasks / internal memory. This builds up into a customizable multi agent system for research that pulls together themes from the entire course.

Course (links to code, all videos):
https://academy.langchain.com/courses/intro-to-langgraph

http://www.tgoop.com/codeprogrammer 🔒

💡 #deeplearning #AI #ML #python

BY Python | Machine Learning | Coding | R




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