01
AI Foundations
Understand what AI is, how systems learn, where they fail, and how to judge claims without hype.
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Five outcome-based courses
Each course includes explicit outcomes, mapped competencies, practice activities, and an applied capstone.
02
Responsible AI User
Use AI productively while protecting privacy, checking outputs, and preserving human accountability.
03
AI at Work
Evaluate workplace use cases, run safe pilots, measure value, and communicate changes responsibly.
04
AI Policy & Society
Analyze AI systems through rights, equity, governance, safety, and public-interest outcomes.
05
Building with AI Systems
Understand language models, retrieval, agents, evaluation, cost, and deployment safeguards through practical system design.
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FundamentalsCore concepts: how AI works at a high level.84 guides Language AILLMs, NLP, ChatGPT, prompting, and text understanding.155 guides Visual AIImage generation, computer vision, video, and design.133 guides Audio AIVoice, music, podcasting, and audio-first AI.117 guides CompaniesProfiles of OpenAI, Anthropic, Google, Meta, and more.121 guides ApplicationsHow AI shows up in coding, search, agents, and daily life.111 guides IndustriesAI in healthcare, finance, education, energy, and more.91 guides TechnicalChips, fine-tuning, RAG, vectors, and AI infrastructure.177 guides SocietyBias, privacy, copyright, safety, and the AI future.30 guides
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Language AI
Part-of-Speech Tagging
Part-of-speech (POS) tagging labels each word in a sentence with its grammatical role, such as noun, verb, or adjective.
Visual AIDALL-E
DALL-E is OpenAI's family of text-to-image models that turn a written description into an original picture.
Visual AICLIP and Vision-Language Models
CLIP is a model from OpenAI that learns to connect images and text by placing both in the same mathematical space.
Visual AINeural Radiance Fields
Neural Radiance Fields (NeRF) reconstruct a full 3D scene from a handful of ordinary photos, letting you fly the camera to brand-new viewpoints.
Visual AIGaussian Splatting
Gaussian Splatting represents a 3D scene as millions of tiny, colored, semi-transparent blobs that can be rendered in real time.
FundamentalsBackpropagation
Backpropagation is the algorithm that lets a neural network learn from its mistakes by efficiently calculating how much each weight contributed to the error.
FundamentalsGradient Descent
Gradient descent is the optimization method that actually moves a model's weights downhill toward lower error, one small step at a time.
FundamentalsLoss Functions
A loss function is the single number that tells a model how wrong its predictions are, turning a vague goal into something math can optimize.
FundamentalsActivation Functions
Activation functions are the small nonlinear gates inside each neuron that let neural networks learn complex, curved patterns instead of just straight lines.
Language AITopic Modeling
Topic modeling is an unsupervised technique that automatically discovers the hidden themes running through a large collection of documents, without anyone…
Language AILanguage Modeling
Language modeling is the deceptively simple task of predicting what word or token comes next, given the text so far.
Language AIBERT and Encoder Models
BERT is a landmark language model that reads text in both directions at once to build rich representations of meaning.
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