AI Literacy Course: Use ChatGPT, Claude & Gemini at Work
Use ChatGPT, Claude, and Gemini with confidence at work: learn the vocabulary, how models work, when to verify them, and reusable prompts. 8 chapters, foundations level.
AI creative pipeline, AI for marketing teams, AI content production at scale, creative ops with AI, multi-platform content engine, AI slide deck design, brand safety AI content, AI asset management course, storytelling at scale
practitioner
en
It is built for marketing and creative professionals, content leads, and creative-ops practitioners who already produce content and want to run AI-assisted production at studio scale. It sits in the AI-by-role marketing track at a practitioner level.
2,33 ore
online
What will I learn in this AI creative pipeline course? You learn to design an end-to-end AI creative production pipeline: asset systems for variants and languages, multi-platform content engines, slide decks built from narrative, storytelling at scale, and QA and brand-safety approval loops. Across 7 chapters you build a repeatable concept-to-delivery studio workflow.
Use ChatGPT, Claude, and Gemini with confidence at work: learn the vocabulary, how models work, when to verify them, and reusable prompts. 8 chapters, foundations level.
A decision-framework deep learning course for engineers. Choose PyTorch vs TensorFlow, judge depth vs classical ML, weigh transfer learning, and reason about CNNs. 7 chapters.
Build production multi-agent systems with the OpenAI Agents SDK and Claude Agent SDK, the engine behind Claude Code. 9 chapters for working engineers.
Ship AI features to production: prompting, RAG, structured outputs, fine-tuning, and inference tuning. Hands-on, free, 12 chapters (~4.3h) for engineers.
Ship AI inside Microsoft Power Platform: AI Builder, Power Apps and Power BI Copilot, Dataverse agents, plus DLP governance. 6 chapters, ~2h, practitioner level.
Build classical ML models that hold up in production. With scikit-learn, learn data splitting, EDA, feature engineering, and algorithm selection across 7 practitioner chapters.
Build production AI agents that use tools, remember across sessions, and recover from failures. Hands-on with MCP, Agent Skills, and agentic RAG, 8 chapters for engineers.
Build real software with AI without writing code: custom assistants, AI agents, dashboards, and clickable prototypes. Hands-on with Claude Code, ChatGPT, and Lovable. 7 chapters…