What Is the AI-901? Glossary & Key Terms

Artificial Intelligence (AI)
Technology that enables software to exhibit human-like behaviors such as perception, reasoning, and decision-making.
Machine Learning (ML)
A branch of AI where algorithms learn patterns from data to make predictions or decisions without being explicitly programmed with rules.
Deep Learning
A subset of machine learning that uses multi-layered neural networks to model complex patterns in large volumes of data.
Neural Network
A computing structure loosely inspired by the brain, composed of layers of interconnected nodes that learn to map inputs to outputs.
Classification
A supervised machine learning task that assigns input data to one of a set of predefined categories.
Clustering
An unsupervised machine learning task that groups similar data points together without predefined labels.
Computer Vision
The AI field concerned with enabling machines to interpret and understand information from images and video.
Object Detection
A computer vision task that locates and classifies multiple objects within an image, typically using bounding boxes.
Optical Character Recognition (OCR)
Technology that extracts printed or handwritten text from images and documents into editable, machine-readable text.
Natural Language Processing (NLP)
The AI discipline focused on enabling computers to understand, interpret, and generate human language.
Sentiment Analysis
An NLP technique that classifies text according to its expressed emotional tone, such as positive, negative, or neutral.
Named Entity Recognition (NER)
An NLP capability that detects and classifies entities such as people, organizations, locations, and dates within text.
Generative AI
AI that produces new content — text, images, audio, or code — by learning the patterns of large training datasets.
Large Language Model (LLM)
A deep learning model trained on vast text corpora that can understand context and generate coherent human-like language.
Prompt Engineering
The practice of crafting and refining input prompts to guide a generative AI model toward more accurate or useful outputs.
Retrieval Augmented Generation (RAG)
A technique that grounds generative model responses by retrieving relevant external data and including it in the prompt context.
Hallucination
An AI-generated output that appears plausible but is factually incorrect or fabricated, not grounded in real source data.
Responsible AI
A framework of principles — fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability — guiding the ethical development of AI systems.
Microsoft Foundry
Microsoft's platform for discovering, customizing, orchestrating, and deploying AI models and agents, including a curated model catalog.
Agentic AI
AI systems capable of autonomously planning and executing multi-step actions or tool calls to achieve a goal with minimal human oversight.
Multi-modal AI
AI that can process and reason over more than one type of input, such as text, images, and audio, within a single model or system.
Bounding Box
A rectangular region drawn around a detected object in an image, used in computer vision to indicate the object's location.