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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Fundamentals
Curriculum Learning
Curriculum learning trains AI models on examples in a deliberate order — easy first, hard later — instead of feeding data in random order.
FundamentalsNeural Architecture Search
Neural Architecture Search (NAS) automates the design of neural network structures — letting algorithms, not humans, decide how many layers, what operations…
FundamentalsContinual Learning and Catastrophic Forgetting
Continual learning is the goal of training AI on a stream of new tasks over time without erasing what it already knows.
Visual AILatent Diffusion Models
Latent diffusion models generate images by running the diffusion process in a compressed latent space instead of raw pixels, slashing compute costs.
Visual AIControlNet
ControlNet is an add-on that gives image-generation models precise structural control, letting you steer output with edges, poses, depth maps, or scribbles.
Visual AIClassifier-Free Guidance
Classifier-free guidance is the technique that makes diffusion models actually follow your prompt, trading some diversity for much stronger adherence.
Visual AIVisual SLAM
Visual SLAM lets a moving camera build a map of an unknown space while simultaneously tracking its own position inside that map.
Visual AISora and Text-to-Video
Sora is OpenAI's text-to-video model that turns a written prompt into a short, high-resolution video clip.
Visual AIVideo Diffusion Models
Video diffusion models generate moving images by gradually turning random noise into coherent frames, extending the diffusion idea from pictures to time.
FundamentalsVariational Autoencoders
Variational autoencoders (VAEs) are generative neural networks that learn to compress data into a smooth, probabilistic latent space and then reconstruct…
FundamentalsState Space Models and Mamba
State space models (SSMs) are sequence models that carry information forward through a compressed hidden state, scaling linearly with sequence length instead…
FundamentalsGraph Neural Networks
Graph neural networks (GNNs) are models that learn directly on graph-structured data — nodes connected by edges — by passing and aggregating information…
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