You'll learn: How to understand and work effectively with AI and ML models and products.
Learning Track information is split up into 4 sections, organized by how it important it is to know each bit; peruse at your own leisure.
Core concepts everyone should understand about AI and ML
Breaking down what ChatGPT and others are doing under the hood
How AI models learned to stop being weird and start being helpful.
A deep dive into how models like ChatGPT get built.
Why these chips pair perfectly with AI, and how NVIDIA became the most valuable company in the world.
AI models inherently make stuff up. What can we do about it?
How computers learn patterns from data — and why it’s the foundation for everything from stock prediction to ChatGPT.
How to make sure your next big AI push doesn't flop.
Enough surveys and corporate hand-waving. Let's answer the question by looking at usage data from an AI compute provider.
What actually goes on inside the buildings propping up the US economy.
How open-weight models went from a curiosity to great in 2 short years.
How generative AI models get built and run
A refresher on how models like ChatGPT and Stable Diffusion work under the hood.
Retrieval Augmented Generation is a way to make AI models more personalized
A vector database is a place where developers store specially formatted data to use for machine learning and AI.
All about "reasoning" language models like OpenAI's o3 and Deepseek's R1.
Key AI tools and platforms
How do ChatGPT, Mistral, Gemini, and Llama3 stack up for common tasks like generating sales emails?
OpenAI isn't the only one having fun
What we should really be asking is “What does Databricks not do?”
How Browserbase built their viral demo of Open Operator (in 24 hrs!) using Vercel's v0 and the AI SDK.
All about Vercel’s v0
The new way of connecting AI models to your tools and data. Is it real, or a passing hype train?
Unlike an onion, hopefully these neural network layers won't make you cry.
How bigger models, more data, and more compute keep beating clever tricks.
Why Three Mile Island is back in action after a 50 year hiatus.
Things you should know as a vibe coder that will make your app actually work / not die.
Comparing Replit, v0, Lovable and Bolt, in a bakeoff to decide who will be Vandalay Industries go-to vibe coding tool.
All about AI evals, plus how Braintrust helps companies build better AI apps.
How to actually make your AI workflows, er, work.
A look at the thin line between using AI smartly and writing your own pink slip.
AI models seem to approximate the brain, intentionally or otherwise.
Finally, an explanation for why AI models can't seem to quit them.
How the rise of open source AI models is fueling the growth of a new infrastructure category.
Why coding agents need a safe place to play, just like we all do.
Why it's surprisingly challenging to let an LLM use a computer for you.
What started as a humble LLM framework has become an everything store for agents.
Core concepts everyone should understand about AI and ML
Breaking down what ChatGPT and others are doing under the hood
How AI models learned to stop being weird and start being helpful.
GPT-3 is a Machine Learning model that generates text.
Data Science Notebooks help data teams explore data with code.
A deep dive into how models like ChatGPT get built.
Why these chips pair perfectly with AI, and how NVIDIA became the most valuable company in the world.
AI models inherently make stuff up. What can we do about it?
How computers learn patterns from data — and why it’s the foundation for everything from stock prediction to ChatGPT.
How to make sure your next big AI push doesn't flop.
Enough surveys and corporate hand-waving. Let's answer the question by looking at usage data from an AI compute provider.
What actually goes on inside the buildings propping up the US economy.
How open-weight models went from a curiosity to great in 2 short years.
How generative AI models get built and run
A refresher on how models like ChatGPT and Stable Diffusion work under the hood.
Beware the benchmark.
Retrieval Augmented Generation is a way to make AI models more personalized
A vector database is a place where developers store specially formatted data to use for machine learning and AI.
All about "reasoning" language models like OpenAI's o3 and Deepseek's R1.
All about Vercel’s v0
The new way of connecting AI models to your tools and data. Is it real, or a passing hype train?
Unlike an onion, hopefully these neural network layers won't make you cry.
How FastMCP makes it easy to ship an MCP server.
How bigger models, more data, and more compute keep beating clever tricks.
Why Three Mile Island is back in action after a 50 year hiatus.
Things you should know as a vibe coder that will make your app actually work / not die.
Comparing Replit, v0, Lovable and Bolt, in a bakeoff to decide who will be Vandalay Industries go-to vibe coding tool.
All about AI evals, plus how Braintrust helps companies build better AI apps.
How to actually make your AI workflows, er, work.
A look at the thin line between using AI smartly and writing your own pink slip.
AI models seem to approximate the brain, intentionally or otherwise.
Finally, an explanation for why AI models can't seem to quit them.
Should I ship something myself, or call in engineering help?
Key AI tools and platforms
How do ChatGPT, Mistral, Gemini, and Llama3 stack up for common tasks like generating sales emails?
OpenAI isn't the only one having fun
OpenAI is the most popular provider of generative AI models like GPT-4.
What we should really be asking is “What does Databricks not do?”
How Browserbase built their viral demo of Open Operator (in 24 hrs!) using Vercel's v0 and the AI SDK.
How the rise of open source AI models is fueling the growth of a new infrastructure category.
Why coding agents need a safe place to play, just like we all do.
Why it's surprisingly challenging to let an LLM use a computer for you.
What started as a humble LLM framework has become an everything store for agents.