I was sick of wasting months on random AI playlists. So I collected the clean free path from zero to being able to build and interview for real roles. Whoever starts now will be ahead of the others. 01 Linear algebra and calculus for ML mml-book.github.io/ 02 Machine learning foundations youtube.com/playlist?list=PL… 03 Deep learning theory deeplearningbook.org/ 04 Neural networks from scratch youtube.com/playlist?list=PL… 05 Computer vision cs231n.stanford.edu/ 06 Natural language processing web.stanford.edu/class/cs224… 07 Transformers and LLMs from scratch cs336.stanford.edu/ 08 Reinforcement learning rail.eecs.berkeley.edu/deepr… 09 Probabilistic machine learning probml.github.io/pml-book/ 10 Building production systems fullstackdeeplearning.com/ 11 Agents huggingface.co/learn/agents-… 12 The full path. Free. You either walk this now or keep collecting playlists for another year. Save this

Stop saving random AI playlists. I’ve put together the best things I’ve come across this year for you This is the actual free path that gets you from zero to being able to build and interview for real AI roles 01 Mathematics for Machine Learning mml-book.github.io/ 02 Probabilistic Machine Learning (Murphy) probml.github.io/pml-book/ 03 Deep Learning Book (Goodfellow) deeplearningbook.org/ 04 Stanford CS229 Machine Learning youtube.com/playlist?list=PL… 05 MIT 6.S191 Introduction to Deep Learning youtube.com/playlist?list=PL… 06 Stanford CS231n Computer Vision cs231n.stanford.edu/ 07 Stanford CS224n Natural Language Processing web.stanford.edu/class/cs224… 08 Stanford CS336 Language Modeling from Scratch cs336.stanford.edu/ 09 Berkeley CS285 Deep Reinforcement Learning rail.eecs.berkeley.edu/deepr… 10 Understanding Deep Learning (Prince) udlbook.github.io/udlbook/ 11 OpenAI Spinning Up (Deep RL) spinningup.openai.com/ 12 Stanford CS25 Transformers United web.stanford.edu/class/cs25/ 13 Full Stack Deep Learning fullstackdeeplearning.com/ 14 Dive into Deep Learning d2l.ai/ 15 The full path. Free. Most people will keep collecting. A few will actually walk this Save this ⭣

I spent 4 months collecting this so you don’t have to waste the same time Most people will save this and never open a single link. This is the clean path from zero to being able to build and interview for real AI roles 01 Linear algebra and calculus mml-book.github.io/ 02 Machine learning foundations youtube.com/playlist?list=PL… 03 Deep learning from scratch youtube.com/playlist?list=PL… 04 Neural networks and backprop youtube.com/watch?v=VMj-3S1t… 05 Computer vision youtube.com/playlist?list=PL… 06 Natural language processing youtube.com/playlist?list=PL… 07 Transformers and LLMs cs336.stanford.edu/ 08 Reinforcement learning rail.eecs.berkeley.edu/deepr… 09 Building agents huggingface.co/learn/agents-… 10 The full path. Free You either walk this now or keep watching random playlists for another year Save this ⭣