Never used AI? Start here. Five things you can do right now, in under 5 minutes each.
Go to chat.openai.com (free). Type "Explain [topic] like I'm 12." Try it with blockchain, quantum computing, or anything you've wondered about. Clear, jargon-free answer in seconds.
Go to claude.ai (free). Paste a long article, report, or email thread. Ask: "Summarize in 5 bullet points." Claude is especially good at handling long documents and pulling out what matters.
In ChatGPT, type "Create an image of [description]." Try: "a cat in a spacesuit on Mars, oil painting style." Generated in seconds. This is DALL-E 3 working behind the scenes.
Tell ChatGPT or Claude: "Help me write a professional email to [person] about [topic]. Keep it friendly but direct." Edit the result to match your voice. Save 10 minutes per email.
Go to perplexity.ai and search something you'd normally Google. Instead of 10 blue links, you get a direct answer with sources cited. Like having a research assistant who reads everything.
Specific AI use cases based on what you actually do for work.
World-class AI courses from MIT, Stanford, Harvard, and top researchers. All completely free.
ANDREJ KARPATHY
Build neural networks from scratch in code — from backpropagation to GPT. By the former Tesla AI Director and OpenAI founding member. The best hands-on AI course that exists.
FreeMIT
MIT's fast-paced deep learning course. Covers neural networks, CNNs, transformers, generative models, and reinforcement learning. Updated every year with new lectures and hands-on labs.
FreeSTANFORD
Andrew Ng's legendary ML course. Supervised learning, unsupervised learning, reinforcement learning, and statistical pattern recognition. The course that launched thousands of ML careers.
FreeSTANFORD
The best free NLP course. Word vectors, transformers, pre-training, reasoning, and agents. Updated annually — the 2024 edition covers LLMs, RLHF, and AI agents.
FreeSTANFORD
Originally created by Fei-Fei Li and Andrej Karpathy. Convolutional neural networks, image recognition, detection, segmentation, and generative models. The definitive computer vision course.
FreeMIT OPENCOURSEWARE
Classic AI foundations — search, constraint satisfaction, logic, planning, and learning. Taught by the legendary Patrick Henry Winston. Full video lectures, assignments, and exams.
FreeHARVARD
Search algorithms, knowledge representation, probability, optimization, ML, neural networks, and NLP. Hands-on Python projects including game dev and handwriting recognition.
FreeFAST.AI
Created by Jeremy Howard (former Kaggle #1). Top-down practical approach — you build real things from lesson 1. Computer vision, NLP, recommendation systems using PyTorch.
FreeANDREW NG / DEEPLEARNING.AI
3-course specialization — the updated version of Ng's original 2012 course. Free to audit on Coursera. Over 4.8 million learners. Rated 4.9/5.
Free to audit15-hour self-study course with animated videos, interactive visualizations, and 130+ exercises. Covers ML fundamentals, large language models, and responsible AI.
FreeUNIVERSITY OF HELSINKI
Non-technical intro to AI for everyone. No programming or advanced math required. Over 1 million students. Perfect starting point if you're completely new to AI.
Free + CertificateGEOFFREY HINTON / U OF TORONTO
Learn neural networks from the "Godfather of Deep Learning" himself. 2024 Nobel Prize winner. Covers architectures, backpropagation, Boltzmann machines, and learning theory.
FreeLearn from the actual researchers building AI. Lectures, paper breakdowns, and visual explanations.
~990K SUBSCRIBERS
Former Tesla AI Director, OpenAI founding member. Deep-dive lectures on LLMs, neural networks, and transformers. His "Zero to Hero" series and 3.5-hour LLM deep dive are landmark content.
LECTURES~6.5M SUBSCRIBERS
Stunning visual math explanations. His neural network series makes backpropagation, gradient descent, and attention mechanisms intuitive. Watch these before any course.
VISUAL MATH~271K SUBSCRIBERS
In-depth 30-minute breakdowns of AI research papers. Transformers, diffusion models, new architectures. The best way to stay current on AI research without reading every paper.
PAPER REVIEWS~1.7M SUBSCRIBERS
AI and computer science breakthroughs explained in short, visual videos. Covers generative AI, simulation, robotics, and more. Complex research made fun and accessible.
QUICK EXPLAINERS~4.9M SUBSCRIBERS
Long-form interviews with the biggest names in AI — Karpathy, LeCun, Altman, Sutskever, Hassabis, Hinton. Direct access to the thinking of the people building AI.
INTERVIEWS~1.3M SUBSCRIBERS
Breaks down statistics and ML into bite-sized visual pieces. If you struggle with the math behind ML, this channel will save you. Unique style that makes complex concepts click.
ML FOUNDATIONSHANDS-ON PYTHON AI
Project-based Python programming for ML and AI. You code along and build real things — neural networks from scratch, TensorFlow, reinforcement learning. Learn by doing.
CODE-ALONGAI NEWS & ANALYSIS
Makes complex AI developments accessible to non-technical audiences. Clear, measured analysis of new model releases, benchmarks, and capabilities. No hype, just signal.
NEWS ANALYSISThe people actually building AI. Follow them for insights you won't find anywhere else.
Founder of Eureka Labs. Former Tesla AI Director, OpenAI founding member. Deep technical insights, educational threads on LLMs and neural networks.
Turing Award laureate. Pioneer of convolutional neural networks. Strong (often contrarian) opinions on AI architecture, AGI timelines, and open-source AI.
NVIDIA Director of AI. Co-lead of Project GR00T (humanoid robotics). Stanford PhD. Brilliant at explaining complex AI research in accessible terms.
Co-founder of Safe Superintelligence Inc. Former OpenAI co-founder and Chief Scientist. Co-invented AlexNet. Posts are rare but carry enormous weight.
CEO of OpenAI. Direct insight into OpenAI's direction, product launches, and the thinking behind one of the most important AI companies.
Co-founder & CEO of Google DeepMind. 2024 Nobel Prize in Chemistry. Built the team behind AlphaGo, AlphaFold, and Gemini.
Stanford Professor. Created ImageNet — the dataset that launched the deep learning revolution. Pioneer of computer vision. Co-founder of World Labs.
Co-founder and CEO of Anthropic (makers of Claude). Former VP of Research at OpenAI — led GPT-2 and GPT-3 teams. Focused on AI safety and responsible development.
MIT researcher and podcast host. Shares clips and insights from interviews with the biggest names in AI. Good for discovering conversations you might have missed.
If you feel overwhelmed, do less. One month of steady use will teach you more than a giant binge of random tutorials.
Use one assistant, one AI search tool, and one real task from your daily work. Practical repetition beats passive reading at the beginning.
No for everyday use. You only need deeper math and code later if you want to build models or move into ML engineering.
Elements of AI and Google's ML Crash Course are accessible beginner options. Karpathy's Zero to Hero and fast.ai are better if you want to build things.