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Start with Let's build GPT: from scratch, in code, spelled out. (116 min, Andrej Karpathy), then Transformers, the tech behind LLMs (27 min, 3Blue1Brown). All 203 lessons here are free, from the teachers' own official uploads. You'll need gpu-ready laptop, laptop stand, noise-cancelling headphones (about $1310 of kit). The book to keep beside you: Deep Learning with Python by Francois Chollet.

What you'll need

• GPU-ready laptop: Train small models locally.
• Laptop stand: Screen at eye level for long study sessions.
• Noise-cancelling headphones: Focus through long video lessons.

Lessons

• Let's build GPT: from scratch, in code, spelled out. (116 min, Andrej Karpathy, Beginner)
• Transformers, the tech behind LLMs | Deep Learning Chapter 5 (27 min, 3Blue1Brown, Intermediate)
• But what is a neural network? | Deep learning chapter 1 (19 min, 3Blue1Brown, Beginner)
• Gradient descent, how neural networks learn | Deep Learning Chapter 2 (21 min, 3Blue1Brown, Intermediate)
• Let's reproduce GPT-2 (124M) (241 min, Andrej Karpathy, Intermediate)
• The spelled-out intro to neural networks and backpropagation: building micrograd (146 min, Andrej Karpathy, Beginner)
• Attention in transformers, step-by-step | Deep Learning Chapter 6 (26 min, 3Blue1Brown, Beginner)
• How might LLMs store facts | Deep Learning Chapter 7 (23 min, 3Blue1Brown, Intermediate)
• Let's build the GPT Tokenizer (134 min, Andrej Karpathy, Intermediate)
• Create a Large Language Model from Scratch with Python – Tutorial (344 min, freeCodeCamp.org, Beginner)
• Backpropagation calculus | Deep Learning Chapter 4 (10 min, 3Blue1Brown, Intermediate)
• Backpropagation, intuitively | Deep Learning Chapter 3 (13 min, 3Blue1Brown, Intermediate)
• The Essential Main Ideas of Neural Networks (19 min, StatQuest with Josh Starmer, Intermediate)
• Transformer Neural Networks, ChatGPT's foundation, Clearly Explained!!! (36 min, StatQuest with Josh Starmer, Intermediate)
• Lec 01. Introduction to Deep Learning (61 min, MIT OpenCourseWare, Beginner)
• Neural Network Simply Explained (11 min, codebasics, Intermediate)
• LLMs from Scratch – Practical Engineering from Base Model to PPO RLHF (366 min, freeCodeCamp.org, Beginner)
• Simple explanation of convolutional neural network (24 min, codebasics, Beginner)
• Day 1- Live Deep Learning Community Session (74 min, Krish Naik, Intermediate)
• Deep Learning Indepth Tutorials In 5 Hours With Krish Naik (342 min, Krish Naik, Intermediate)
• Neural Networks Part 8: Image Classification with Convolutional Neural Networks (CNNs) (15 min, StatQuest with Josh Starmer, Intermediate)
• Recurrent Neural Networks (RNNs), Clearly Explained!!! (17 min, StatQuest with Josh Starmer, Intermediate)
• Stanford CS230 | Autumn 2025 | Lecture 1: Introduction to Deep Learning (60 min, Stanford Online, Beginner)
• Transformers Explained | Simple Explanation of Transformers (58 min, codebasics, Beginner)
• Day 2-Forward Propogation, Loss Functions, Chain Rule Of Derivatives|Deep Learning Live (105 min, Krish Naik, Intermediate)
• Python + PyTorch + Pygame Reinforcement Learning – Train an AI to Play Snake (99 min, freeCodeCamp.org, Intermediate)
• Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial (114 min, freeCodeCamp.org, Intermediate)
• Self-Driving Car with JavaScript Course – Neural Networks and Machine Learning (153 min, freeCodeCamp.org, Intermediate)
• Day 3- Optimizers And ANN Implementation| Live Deep Learning Community Session (64 min, Krish Naik, Intermediate)
• The spelled-out intro to language modeling: building makemore (118 min, Andrej Karpathy, Beginner)
• The StatQuest Introduction to PyTorch (23 min, StatQuest with Josh Starmer, Beginner)
• Become an AI Researcher Course – LLM, Math, PyTorch, Neural Networks, Transformers (187 min, freeCodeCamp.org, Intermediate)
• Computer Vision and Perception for Self-Driving Cars (Deep Learning Course) (120 min, freeCodeCamp.org, Intermediate)
• Day 4-Practical ANN Impementation| Live Deep Learning Community Session (75 min, Krish Naik, Intermediate)
• Deep Learning Course for Beginners (829 min, freeCodeCamp.org, Beginner)
• Learn PyTorch in 5 Projects – Tutorial (349 min, freeCodeCamp.org, Intermediate)
• What is a neuron? (17 min, codebasics, Beginner)
• What is BERT? (23 min, codebasics, Beginner)
• Activation Functions (16 min, codebasics, Intermediate)
• Backpropagation Details Pt. 2: Going bonkers with The Chain Rule (13 min, StatQuest with Josh Starmer, Intermediate)
• Coding a ChatGPT Like Transformer From Scratch in PyTorch (31 min, StatQuest with Josh Starmer, Beginner)
• Decoder-Only Transformers, ChatGPTs specific Transformer, Clearly Explained!!! (37 min, StatQuest with Josh Starmer, Intermediate)
• Neural Networks Pt. 2: Backpropagation Main Ideas (18 min, StatQuest with Josh Starmer, Intermediate)
• Tensors for Neural Networks, Clearly Explained!!! (10 min, StatQuest with Josh Starmer, Intermediate)
• Understanding Deep Learning Research Tutorial - Theory, Code and Math (106 min, freeCodeCamp.org, Intermediate)
• 1: Introduction to Neural Networks and Deep Learning; Training Deep NNs (57 min, MIT OpenCourseWare, Beginner)
• Building a Vision Transformer Model from Scratch with PyTorch (125 min, freeCodeCamp.org, Beginner)
• Building makemore Part 2: MLP (76 min, Andrej Karpathy, Intermediate)
• Building makemore Part 3: Activations & Gradients, BatchNorm (116 min, Andrej Karpathy, Intermediate)
• Day 5-Understanding CNN &Impementation| Live Deep Learning Community Session (74 min, Krish Naik, Intermediate)
• Essential Matrix Algebra for Neural Networks, Clearly Explained!!! (30 min, StatQuest with Josh Starmer, Intermediate)
• Gradient Descent For Neural Network (42 min, codebasics, Intermediate)
• Hot Dog or Not Hot Dog – Convolutional Neural Network Course for Beginners (88 min, freeCodeCamp.org, Beginner)
• Image classification using CNN (CIFAR10 dataset) (28 min, codebasics, Intermediate)
• Neural Networks Part 5: ArgMax and SoftMax (14 min, StatQuest with Josh Starmer, Intermediate)
• Precision, Recall, F1 score, True Positive|Deep Learning Tutorial 19 (Tensorflow2.0, Keras & Python) (12 min, codebasics, Intermediate)
• Attention for Neural Networks, Clearly Explained!!! (16 min, StatQuest with Josh Starmer, Intermediate)
• Complete Transformers For NLP Deep Learning One Shot With Handwritten Notes (301 min, Krish Naik, Intermediate)
• Deep Learning Vision Architectures Explained – Python Course on CNNs and Vision Transformers (307 min, freeCodeCamp.org, Intermediate)
• Diffusion Models for AI Image Generation (12 min, IBM Technology, Intermediate)

Books on Deep Learning

1. Deep Learning with Python by Francois Chollet - View on Amazon
2. Deep Learning by Ian Goodfellow - View on Amazon