Every AI Model Explained
Tina Huang. A calm 19-minute map of the major model families — OpenAI's GPT line, Anthropic's Claude, Google's Gemini, plus the open-source players — and which tier inside each family is worth your time. After the article tells you "pick one and stick with it for a month," this video tells you what the dropdown menu inside that one is actually offering. Honestly opinionated without being a hot take.
AI Expert note
Model names, rankings and default choices are especially unstable. Keep the beginner rule: choose a mainstream product that fits the job, then evaluate outputs on your own examples instead of trusting leaderboard claims.
What you should get from this
Understand the product and model-family landscape well enough to choose one starting tool and stop endlessly comparing tabs.
Watch or know first
Basic awareness that a chatbot product and the model selected inside it are different decisions.
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Continue through the same learning path with the next curated companion videos.
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A longer, more patient course that earns its length.
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Use AI to draft email faster, then pressure-test tone and clarity from the recipient's point of view.
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Take it further
Hand-picked external courses that go deeper on this topic.
Coursera · DeepLearning.AIGenerative AI for Everyone
Real time inside an LLM, learning to prompt deliberately and recognise where generative AI is genuinely useful versus where it's a trap. Calm, no-hype teaching — the perfect bridge from "I've tried ChatGPT once" to "I use it every day with confidence."
Coursera · DeepLearning.AI + AWSGenerative AI with Large Language Models
When practitioners ask "what should I take if I'm serious about building with LLMs?", this is the answer. Mathematically honest without being a research paper; AWS-flavoured deployment chapters stay useful even if you'll never touch SageMaker.
Anthropic AcademyMCP: Build Rich-Context AI Apps with Anthropic
MCP is the protocol that's quietly replacing one-off tool integrations across the AI tooling ecosystem. Learn it from the source. By the end you'll have built and deployed your own MCP server, connected an LLM client to it, and understood why this standard is the closest thing the field has to USB-C.