Large models (LLMs, diffusion models, etc.) are impressive, but also compute-hungry, memory-intensive, and often hard to deploy on real-world devices.

That’s why this MIT course on Efficient ML is a must for anyone serious about scalable, accessible AI.

🎯 Learn the core techniques to make AI fast, light, and deployable:
• Compression & Pruning
• Quantization
• Neural Architecture Search
• Distributed & Parallel Training
• On-device Fine-tuning
• Gradient Compression
• Acceleration for LLMs, diffusion, video, point cloud
• Even Quantum ML

✔️ Hands-on project: Deploy LLaMA 2 on your laptop.

🔗 Take the course:
https://youtube.com/playlist?list=PL80kAHvQbh-pT4lCkDT53zT8DKmhE0idB