AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Free AI library
133 plain-English guides, structured learning paths, and an open library — built by an independent 501(c)(3) nonprofit so anyone can understand modern AI.
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Each course includes explicit outcomes, mapped competencies, practice activities, and an applied capstone.
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
Topic tracks
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CycleGAN learns to translate images between two visual domains (like horses to zebras, or photos to paintings) without ever needing matched before-and-after…
Visual AISPADE (Spatially-Adaptive Normalization) turns a simple labeled layout, like a child's coloring-book map of 'sky here, grass there, tree here'…
Visual AIDragGAN lets you edit an image by literally dragging points: grab a spot and drag it to a target, and the picture deforms realistically, changing pose…
Visual AIDiffusion Transformers (DiTs) swap the convolutional U-Net at the heart of image and video generators for a Transformer backbone.
Visual AIFeature Pyramid Networks (FPN) let detectors spot objects at wildly different sizes by building a multi-scale 'pyramid' of features cheaply.
Visual AINon-Maximum Suppression (NMS) is the cleanup step that turns a messy pile of overlapping detection boxes into one tidy box per object.
Visual AISpatial Transformer Networks (STNs) are learnable modules that let a neural network actively warp, rotate, crop, or rescale its input to focus on what…
Visual AIStereo depth estimation recovers how far away things are by comparing two slightly offset camera views, just like your two eyes do.
Visual AIA point cloud is a set of 3D points (X, Y, Z) that captures the shape of real objects and spaces, often from LiDAR or depth sensors.
Visual AIA signed distance function (SDF) describes a 3D shape by telling you, for any point in space, how far it is to the nearest surface, with a sign that says…
Visual AIDeformable convolutions let a neural network bend its sampling grid to follow the actual shape of objects instead of forcing it through a rigid square window.
Visual AIDINO is a self-supervised method that trains a vision transformer to understand images with no labels at all, by having the network teach itself.
Check what you learned with topic quizzes, then explore our structured courses and current certification requirements. Core guides remain free to read.