@gneubig: This Fall at CMU we're teaching a new course on AI Agents! The goal is that you learn how to create a scaffold, build e…
Summary
Carnegie Mellon University is offering a new fall course on AI Agents, covering scaffolding, evals, and training agentic LLMs using reinforcement learning, balancing theory and practice.
View Cached Full Text
Cached at: 07/02/26, 08:25 PM
This Fall at CMU we’re teaching a new course on AI Agents!
The goal is that you learn how to create a scaffold, build evals, and train an agentic LLM using RL.
We’ll try to balance theory and practice, and introduce modern frameworks and best practices. https://t.co/iPr8FMD5wp
Similar Articles
@Alacritic_Super: Carnegie Mellon University's 11-768: AI Agents is one of the most comprehensive free courses on building LLM-based agen…
Carnegie Mellon University offers a comprehensive free course on building LLM-based agents, covering topics from prompting to production systems.
@omarsar0: The best way to learn AI is to build with agents. To help with that, we've launched hands-on labs and a new series on A…
Launches hands-on labs and a series on Agentic Engineering, starting with Agent Skills, covering planning, context engineering, multi-agent systems, and long-running agents.
@tom_doerr: Teaches building AI agents from first principles https://github.com/pguso/ai-agents-from-scratch…
A GitHub repository that teaches how to build AI agents from first principles using local LLMs and node-llama-cpp, progressing from basic LLM interactions to full agent architectures like ReAct.
@0xCodez: Google just dropped a 1-hour course on agentic engineering from scratch: 00:00 – How to build your first AI agent 08:24…
Google released a free 1-hour course on agentic engineering, covering building AI agents, implementing memory, agentic loops, MCP vs API, and multi-agent systems.
@askgpts: Google just dropped a free 11 video crash course on AI agents and it's actually worth your time most tutorials teach yo…
Google released a free 11-video crash course on AI agents covering design patterns, memory, evaluation, multi-agent coordination, and MCP servers, focused on production architecture.