Modules
Every module across every protocol, in one place. Search by topic or filter by level to find what you need.
29 modules found
Why AI Matters (to You)
Work, fear, opportunity, why you need to understand AI now.
How Machines Learn
Supervised, unsupervised, reinforcement, how machines learn.
Neural Networks Intro
Neurons, layers, activation, how a neural network works.
Training and Evaluation
Loss, optimizer, metrics, evaluating a model.
Deep Networks
Why go deep? Vanishing gradients, skip connections, batch norm.
Convolutional Networks
How AI sees images: convolutions, feature maps, transfer learning.
Recurrent Networks
Sequences and memory: RNN, LSTM, and the road to attention.
Generative Models
Creating content: GANs, VAEs, Diffusion.
From Text to Tokens
Models can't read words: how text becomes numbers.
Embeddings
From token IDs to meaning: vectors, semantic space, context.
The Transformer
The architecture that changed everything: attention is all you need.
Language Models
GPT, BERT, and the large language model revolution.
From Base Model to Assistant
Pretraining, fine-tuning, RLHF: how ChatGPT is actually made.
Prompt Engineering
The science behind prompts: few-shot, chain-of-thought, debugging.
Working with APIs
Request-response, streaming, tool use, structured outputs, costs.
RAG & Knowledge
Giving models knowledge they were never trained on.
AI Agents
Autonomous agents: loops, tool calling, memory, multi-agent.
MCP & Orchestration
Connecting AI to everything: MCP, workflows, AI-assisted coding.
Fine-tuning & Customization
When and how to customize an AI model.
Evaluating AI
Can you trust it? Hallucinations, verification, evals.
Why AI Fails
Know your target: how and why models break.
Prompt Injection
The #1 vulnerability of LLM apps, and why it's still unsolved.
Jailbreaking & Red Teaming
Bypassing guardrails, and doing it responsibly.
Attacking the Model
Attacks on training data, weights, and privacy.
Agentic Security
Securing agents: tools, MCP, permissions, blast radius.
Defending AI Systems
The defender playbook: guardrails, filtering, evals, architecture.
Ethics & Responsibility
Bias, privacy, automated decisions, regulation.
Learning to Learn AI
The meta-skill: evaluating tools, spotting hype, staying current.
AI Literacy
Reading papers, spotting hype, understanding the ecosystem.