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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Companies
Zhipu GLM Models
Zhipu AI is a Tsinghua-spun Beijing company behind the GLM (General Language Model) family.
CompaniesTencent Hunyuan
Hunyuan is Tencent's in-house family of large AI models spanning text, image, 3D, and video.
TechnicalKubeflow and ML Pipeline Orchestration
Kubeflow is an open-source toolkit that runs machine learning workflows on Kubernetes, turning model training and deployment into reproducible, containerized…
TechnicalApache Airflow for ML Workflows
Apache Airflow is an open-source platform for authoring, scheduling, and monitoring workflows as code.
TechnicalMLflow and Model Lifecycle Tracking
MLflow is an open-source platform for managing the machine learning lifecycle, from experiment tracking to model packaging and deployment.
TechnicalExpert Parallelism for MoE Serving
Expert parallelism splits a Mixture-of-Experts model's many feed-forward 'experts' across different GPUs so each device holds only a slice of the parameters.
TechnicalSequence Parallelism and Ring Attention
Sequence parallelism splits a single long input sequence across multiple GPUs along the token (time) dimension, and Ring Attention lets those GPUs compute…
TechnicalActivation Recomputation Tradeoffs
Activation recomputation (gradient or activation checkpointing) saves GPU memory during training by discarding intermediate activations in the forward pass…
IndustriesAI in Veterinary Medicine
AI helps veterinarians read X-rays, flag disease earlier, and manage the crushing paperwork of a clinic.
IndustriesAI in Nursing
AI supports nurses with documentation, early-warning alerts on deteriorating patients, and smarter staffing, freeing them for hands-on care.
IndustriesAI in Elder Care
AI helps older adults stay safe and independent at home through fall detection, medication reminders, and companionship tools, while supporting caregivers.
IndustriesAI in Forestry
AI helps foresters monitor vast woodlands from satellites and drones, detect wildfires and pests early, and plan sustainable harvests.
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