@PierceZhang34: Top AI Agent Learning Resources (YouTube) Mu Li | Chief Scientist at Amazon Favorite for hands-on learners! "Hands-on AI Agent" Series Build multi-agent collaboration frameworks from scratch with PyTorch, industrial-grade task scheduling and real-time decision-making code fully open-source, with complete Jupyter...

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Recommends YouTube Agent learning resources from top AI experts like Mu Li, Hung-yi Lee, Andrej Karpathy, Hugging Face official channel, Andrew Ng, Song Han, etc., covering building multi-agent frameworks from scratch, open-source code, practical cases, etc.

Top AI Agent Learning Resources (YouTube) Mu Li | Chief Scientist at Amazon Favorite for hands-on learners! The "Hands-on AI Agent" series uses PyTorch to build multi-agent collaboration frameworks from scratch, with industrial-grade task scheduling and real-time decision-making code fully open-source, including complete Jupyter Notebook. It provides line-by-line deep reading of AutoGPT and ReAct, hands-on deconstruction of agent memory flow and tool invocation logic, enabling beginners to quickly get started. Hung-yi Lee | Professor at National Taiwan University Best for zero-based beginners! The "AI Agent System Design 2025" series uses the "Avengers" as a metaphor for multi-agent collaboration and the "Harry Potter Patronus Charm" to explain tool invocation, making abstract concepts vivid and easy to understand, combining fun with depth. Andrej Karpathy | OpenAI Founding Member A godsend for hardcore tech enthusiasts! The "From LLMs to Agents" series takes you from scratch to building the complete AutoGPT architecture, implementing recursive task decomposition in 4 hours, and reproducing trending GitHub projects. Live debugging of agent infinite loops, using VS Code breakpoints to trace tool call chains — packed with practical content. Hugging Face Official Channel A must-watch for systematic learning of agent frameworks! The "Master Agent Frameworks in 10 Hours" course focuses on Transformers Agent in practice, teaching you to quickly deploy your personal AutoGPT with GPU. Also includes multiple special topics covering real-world scenarios like multi-agent auction systems and stock analysis robots. Andrew Ng | DeepLearning.AI Favorite for logic organizers! The "AI Agent Specialized Course" uses Excel to visualize agent decision trees, clearly and thoroughly explaining the process of complex task decomposition. Also previews a new course "Multi-Agent Game Theory Systems" that supports running AutoGPT-like clusters locally. MIT Efficient ML (Song Han | MIT Professor) A paradise for edge computing + agent enthusiasts! The "Edge Computing Agent" series teaches you to deploy Llama3-powered agents to Raspberry Pi, quantized to only 2GB of memory, giving small devices powerful intelligence.
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Top AI Agent Learning Resource Recommendations (YouTube)

Mu Li (李沐) | Chief Scientist at Amazon
Best for hands-on learners! The “Hands-On AI Agent” series builds multi-agent collaboration frameworks from scratch using PyTorch, with industrial-grade task scheduling, real-time decision-making code fully open-sourced, complete with Jupyter Notebooks. Sentence-by-sentence deep dives into AutoGPT and ReAct, step-by-step breakdowns of agent memory streams and tool invocation logic — beginners can quickly get up to speed.

Hung-yi Lee (李宏毅) | Professor at National Taiwan University
Best for zero-to-hero! The “AI Agent System Design 2025” series uses “Avengers” metaphors for multi-agent collaboration and “Harry Potter’s Patronus Charm” to explain tool calls. Abstract concepts instantly become vivid and understandable — a perfect blend of fun and depth.

Andrej Karpathy | OpenAI Founding Member
A godsend for hardcore tech enthusiasts! The “From LLMs to Agents” series walks you through building the complete AutoGPT architecture from scratch, implements recursive task decomposition in 4 hours, and even replicates a GitHub trending project. Live debugging of agent infinite loops in real time, VS Code breakpoints to trace tool invocation chains — packed with pure干货.

Hugging Face Official Channel
A must-watch for systematic learning of agent frameworks! “Master Agent Frameworks in 10 Hours” focuses on Transformers Agent in practice, teaching you to quickly deploy a personal AutoGPT on GPU. Also covers multi-topic content including multi-agent auction systems, stock analysis bots, and other real-world scenarios.

Andrew Ng (吴恩达) | DeepLearningAI
Best for logic-oriented learners! The “AI Agent Specialization” visualizes agent decision trees in Excel, explaining complex task decomposition clearly and thoroughly. Also previews a new course “Multi-Agent Game Systems”, which supports running an AutoGPT-like cluster locally.

MIT Efficient ML (韩松 | MIT Professor)
A paradise for edge computing + agent enthusiasts! The “Edge Computing Agents” series teaches you to deploy a Llama3-driven agent on a Raspberry Pi, quantized to only 2GB of memory — bringing powerful intelligence to small devices.

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