AI/ML Video Learning Resources 🎥

Essential video courses and tutorials from top educators and institutions.

🎓 University Courses (Full Courses)

Stanford CS229: Machine Learning

Instructor: Andrew Ng
Link: https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
Classic ML foundations - linear regression, logistic regression, SVMs, neural networks

Stanford CS224N: NLP with Deep Learning

Instructor: Christopher Manning
Link: https://www.youtube.com/playlist?list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ
RNNs, transformers, BERT, attention mechanisms, language models

Stanford CS231N: Computer Vision

Link: https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv
CNNs, image classification, object detection, segmentation

MIT 6.S191: Intro to Deep Learning

Link: https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI
Fast-paced overview of deep learning fundamentals and applications

MIT 6.006: Introduction to Algorithms

Link: https://www.youtube.com/playlist?list=PLUl4u3cNGP61Oq3tWYp6V_F-5jb5L2iHb
Essential algorithms and data structures

MIT 18.06: Linear Algebra

Instructor: Gilbert Strang
Link: https://www.youtube.com/playlist?list=PL49CF3715CB9EF31D
The classic linear algebra course

DeepMind x UCL: Deep Learning

Link: https://www.youtube.com/playlist?list=PLqYmG7hTraZCDxZ44o4p3N5Anz3lLRVZF
Advanced deep learning from DeepMind researchers

🧠 Neural Networks Deep Dives

3Blue1Brown - Neural Networks

Link: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
Must Watch! Best visual explanations of how neural networks work
Topics: Neurons, gradient descent, backpropagation, calculus intuition

Andrej Karpathy - Neural Networks: Zero to Hero

Link: https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ
Build from scratch! Code-first approach to understanding LLMs

  • Micrograd (autograd engine)

  • Makemore (character-level language models)

  • Let’s build GPT - Build GPT from scratch in PyTorch

🤖 Generative AI & LLMs

DeepLearning.AI Short Courses

Link: https://www.deeplearning.ai/short-courses/
Free hands-on courses (1-2 hours each):

  • ChatGPT Prompt Engineering for Developers

  • LangChain for LLM Application Development

  • Building RAG Applications with LangChain

  • Finetuning Large Language Models

  • Vector Databases from Embeddings to Applications

Hugging Face Course

Link: https://huggingface.co/learn/nlp-course
Complete guide to transformers, tokenization, fine-tuning with videos

Sam Witteveen - LangChain & LLMs

Link: https://www.youtube.com/@samwitteveenai
Practical LLM tutorials, RAG implementations

James Briggs - Vector Databases

Link: https://www.youtube.com/@jamesbriggs
Vector databases, semantic search, LLM engineering

📊 Math & ML Fundamentals

StatQuest with Josh Starmer

Link: https://www.youtube.com/c/joshstarmer
Best for: Understanding ML concepts simply
Topics: PCA, SVMs, decision trees, random forests, gradient boosting, neural networks

3Blue1Brown Math Series

Khan Academy

Link: https://www.khanacademy.org/math/linear-algebra
Linear algebra, statistics, calculus fundamentals

Professor Leonard

Link: https://www.youtube.com/@ProfessorLeonard
Comprehensive calculus series

Steve Brunton

Link: https://www.youtube.com/@Eigensteve
Control theory, SVD, dynamic mode decomposition

🔬 AI Research & Paper Reviews

Two Minute Papers

Link: https://www.youtube.com/c/KárolyZsolnai
Latest AI research explained in 2-5 minutes
Topics: New papers on diffusion models, NeRFs, GANs, transformers

Yannic Kilcher

Link: https://www.youtube.com/@YannicKilcher
In-depth paper reviews (Attention is All You Need, GPT-3, etc.)

Arxiv Insights

Link: https://www.youtube.com/@ArxivInsights
Research paper summaries

AI Coffee Break with Letitia

Link: https://www.youtube.com/@AICoffeeBreak
AI ethics and research

🛠️ Practical Coding

sentdex

Link: https://www.youtube.com/user/sentdex
Python ML tutorials, deep learning from scratch

Nicholas Renotte

Link: https://www.youtube.com/c/NicholasRenotte
Computer vision projects, TensorFlow tutorials

Aladdin Persson

Link: https://www.youtube.com/@AladdinPersson
PyTorch paper implementations with clear walkthroughs

Abhishek Thakur

Link: https://www.youtube.com/@abhishekkrthakur
Kaggle grandmaster - competition strategies, end-to-end ML

Krish Naik

Link: https://www.youtube.com/user/krishnaik06
MLOps, deployment, production ML systems

🏢 Production & MLOps

Made With ML

Link: https://www.youtube.com/@madewithml
MLOps by Goku Mohandas

ML System Design Interview

Link: https://www.youtube.com/@MLSystemDesignInterview
Production ML systems and architecture

Neptune.ai

Link: https://www.youtube.com/@neptune-ai
MLOps best practices

💼 Career & Interview Prep

Data Science Jay

Link: https://www.youtube.com/@DataScienceJay
Data science interview preparation

Tina Huang

Link: https://www.youtube.com/@TinaHuang1
Data science career advice

🎯 Quick Start Paths

Complete Beginner (Math + ML):

  1. 3Blue1Brown - Neural Networks

  2. StatQuest - ML fundamentals

  3. Stanford CS229 (first 10 lectures)

Deep Learning Focus:

  1. MIT 6.S191

  2. Andrej Karpathy - Neural Networks: Zero to Hero

  3. Stanford CS231N or CS224N

GenAI/LLMs:

  1. Andrej Karpathy - Let’s build GPT

  2. DeepLearning.AI - LangChain course

  3. Hugging Face transformers course

Production ML:

  1. Made With ML

  2. ML System Design Interview

  3. Krish Naik - MLOps

Stay Updated:

  • Subscribe to Two Minute Papers

  • Follow Yannic Kilcher for paper reviews

  • Matthew Berman for tools/local LLMs

📌 Must-Watch Single Videos

Pro Tip: Watch at 1.5-2x speed once you get the basics!