AI Vocabulary Cheat Sheet
27 essential AI terms in plain English, grouped by theme: core concepts, how models learn, using AI tools, and risks and limits.
Cheat Sheets
Quick references for tools, concepts, and workflows.
27 essential AI terms in plain English, grouped by theme: core concepts, how models learn, using AI tools, and risks and limits.
A one-page checklist for using AI assistants safely — what to share, what to connect, and what to verify.
The frontier embedding models, and how they're actually rated: MTEB, Recall@K, NDCG, and Matryoshka truncation in plain English.
Six reusable prompt patterns — role, few-shot, chain-of-thought, output format, refinement, decomposition — each with a copy-paste template.
The everyday Linux command set on one page: navigation, files, permissions, processes, networking, disk, and the pipes that glue them together.
A practical checklist for using AI responsibly at school or work: verification, privacy, disclosure, bias awareness, and judgment.
The daily Git command set on one page: the status-add-commit loop, branching, remotes, undo at every stage, stash, and history archaeology.
A one-page reference for ML fundamentals: the workflow, types of learning, common algorithms, evaluation basics, and when not to use ML.
The Security+ SY0-701 exam on one page: the five domains and weightings, high-yield concepts per domain, and the acronyms and ports the exam expects you to know cold.
The CISSP CAT exam on one page: the eight domains and weightings, the high-yield concepts per domain, and the manager's-mindset approach the exam actually rewards.
The CCNA 200-301 exam on one page: current domains and weightings, the high-yield facts per domain, and a clear heads-up on the v2.0 change coming in 2027.
20 machine learning terms in plain English: features, labels, overfitting, gradient descent, hyperparameters, and more.
The one-page prompting reference: anatomy of a good prompt, a quick checklist, copy-paste templates, and fixes for common failures.