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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Applications
AI in Pest and Invasive Species Detection
AI identifies harmful insects, weeds, diseases, and invasive animals from images, sounds, and sensor data so they can be caught early.
ApplicationsAI in Counterfeit Product Detection
AI spots fake goods, from luxury handbags to medicines and electronics, by analyzing images, packaging, listings, and microscopic material patterns.
CompaniesServiceNow and StarCoder
StarCoder is an open large language model for code, built by ServiceNow Research and Hugging Face through the BigCode project.
CompaniesBigScience and the BLOOM Model
BigScience was a year-long open research collaboration of over 1,000 researchers that produced BLOOM, one of the first truly multilingual, openly released…
CompaniesLAION and Open Datasets
LAION is a German nonprofit that released massive open image-text datasets, most famously LAION-5B, which fueled the training of open generative models like…
Visual AIGigaGAN Scaled Generators
GigaGAN is a billion-parameter GAN that proves generative adversarial networks can scale to text-to-image generation, rivaling diffusion models…
Visual AIVQGAN and Codebook Image Synthesis
VQGAN compresses images into a grid of discrete tokens drawn from a learned codebook, letting a transformer generate images the same way language models…
Visual AIMaskGIT Parallel Token Decoding
MaskGIT generates images by predicting many tokens at once and filling in the most confident ones first, replacing slow left-to-right generation…
TechnicalLinear Attention and Performer Kernels
Linear attention replaces the quadratic softmax attention in Transformers with a math trick that scales linearly with sequence length.
TechnicalYaRN and Context Length Extension
YaRN (Yet another RoPE extensioN) is an efficient technique for stretching a model's usable context window far beyond what it was trained on.
TechnicalPositional Interpolation for Long Context
Positional Interpolation (PI) is a simple, influential technique that extends a Transformer's context window by squeezing new position indices into the range…
CompaniesContextual AI Enterprise RAG
Contextual AI builds end-to-end retrieval-augmented generation (RAG) systems for enterprises, founded by the researchers who coined the term RAG.
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