AI Glossary

Core terms referenced throughout PAII's certification curricula, explained in plain language.

Artificial Intelligence (AI)

Computer systems designed to perform tasks that typically require human intelligence, such as understanding language, recognizing patterns, or making decisions.

Machine Learning (ML)

A branch of AI where systems learn patterns from data rather than following explicitly programmed rules, improving their performance as they see more examples.

Neural Network

A machine learning model loosely inspired by the structure of the brain, made up of layers of connected nodes that learn to recognize patterns in data.

Large Language Model (LLM)

A neural network trained on vast amounts of text, capable of understanding and generating human language — the technology behind tools like ChatGPT.

Prompt Engineering

The practice of crafting inputs to an AI system — especially an LLM — to reliably get useful, accurate, and relevant outputs.

Generative AI

AI systems that create new content — text, images, audio, or code — rather than only analyzing or classifying existing data.

AI Ethics

The study and practice of ensuring AI systems are developed and used fairly, transparently, and responsibly, minimizing bias and harm.

Data Analytics

The process of examining data sets to draw conclusions and support decision-making, often a foundation for applying AI effectively in business.