awesome-aigc-tutorials
github.com/luban-agi/awesome-aigc-tutorials ↗Curated tutorials and resources for Large Language Models, AI Painting, and more.
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me 🔬 theory of llms resources from awesome-aigc-tutorials"
Installation instructions →What's inside
💬 Large Language Models
- 11-667: Large Language Models Methods and Applications - Carnegie Mellon University🔬 Theory of LLMs
Carnegie Mellon University
- Building Systems with the ChatGPT API - DeepLearning.AI💡 Prompt Engineering
DeepLearning.AI
- ChatGPT Prompt Engineering for Developers - DeepLearning.AI💡 Prompt Engineering
DeepLearning.AI
- COS 597G (Fall 2022): Understanding Large Language Models - Princeton University🔬 Theory of LLMs
Princeton University
- CS11-711 Advanced Natural Language Processing - Carnegie Mellon University🔬 Theory of LLMs
Carnegie Mellon University
- CS224N: Natural Language Processing with Deep Learning - Stanford University🔬 Theory of LLMs
Stanford University
🌈 Multimodal
- 11-777: MultiModal Machine Learning (Fall 2022) - Carnegie Mellon University
Carnegie Mellon University
- 11-877: Advanced Topics in MultiModal Machine Learning (Fall 2022) - Carnegie Mellon University
Carnegie Mellon University
- CSCI-GA.3033-102 Special Topic - Learning with Large Language and Vision Models
Learning with Large Language and Vision Models
- Tutorial on MultiModal Machine Learning (ICML 2023) - Carnegie Mellon University
Carnegie Mellon University
💻 AI System
- 15-849: Machine Learning Systems - Carnegie Mellon University
Carnegie Mellon University
- AI-Sys-Sp22 Machine Learning Systems - University of California, Berkeley
University of California, Berkeley
- AI-Systems (LLM Edition) 294-162 - University of California, Berkeley
University of California, Berkeley
- Computer Science 598D - Systems and Machine Learning - Princeton University
Systems and Machine Learning - Princeton University
- CS 329S: Machine Learning Systems Design - Stanford University
Stanford University
- Deep Learning Systems: Algorithms and Implementation - Tianqi Chen, Zico Kolter
Tianqi Chen, Zico Kolter
🧠 Deep Learning
- 6.S191: Introduction to Deep Learning - Massachusetts Institute of Technology
Massachusetts Institute of Technology
- CS25: Transformers United V2 - Stanford University
Stanford University
- Deep Learning Lecture Series 2020 - DeepMind x University College London
DeepMind x University College London
- Deep Learning Specialization - Andrew Ng
Andrew Ng
- Neural Networks - 3Blue1Brown
3Blue1Brown
- Neural Networks/Deep Learning - StatQuest
StatQuest
👋 Introduction
- AI for Everyone - Andrew Ng
Andrew Ng
- Artificial Intelligence for Beginners - Microsoft
Microsoft
- Generative AI learning path - Google Cloud
Google Cloud
- Practical AI for Teachers and Students - Wharton School
Wharton School
🗂 Miscellaneous
- Codefuse-ChatBot🤝 Friendship Links
- Codefuse DevOps Eval🤝 Friendship Links
- WayToAGI🤝 Friendship Links
🔊 AI Audio
🎨 AI Painting
- How Diffusion Models Work - DeepLearning.AI🌊 Stable Diffusion Principles and Applications
DeepLearning.AI
- Hugging Face Diffusion Models Course🌊 Stable Diffusion Principles and Applications
- Lecture Series: An interesting topic every week on the fundamentals of art - Niji Academy🧑🎨 Art Fundamentals and AI Painting Techniques
Niji Academy
- Practical Deep Learning for Coders part 2: Deep Learning Foundations to Stable Diffusion - fast.ai🌊 Stable Diffusion Principles and Applications
fast.ai
Showing a sample of 52 resources. View the full list on GitHub →