Deep Learning
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.
AI for leaders course, AI strategy for executives, build vs buy vs partner AI, AI investment thesis ROI, AI org design and talent, AI risk governance for boards, AI transformation leadership, executive AI decision framework, AI strategy for CHROs and CFOs
advanced
en
It is for executives and senior leaders, including CEOs, CHROs, CFOs, and board members, who decide how their organization invests in and governs AI. It is an advanced, business-focused course rather than a technical one.
Course Mode: online · Course Workload: PT101M · Mode: online
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.
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.
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 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, beginner.
Understand how tools, memory, and goals turn a chatbot into an AI agent that does work, why agents fail, and how to direct them. No code. 6 chapters, ~95 min, no experience needed.
Run AI directly on a phone or Mac with no cloud round-trip. Build with Apple Foundation Models, Gemini Nano, and MLX across 4 advanced chapters for app engineers.
Build and ship custom AI agents in Microsoft Copilot Studio: topics, RAG knowledge sources, connectors, actions, and DLP governance. 4 chapters, practitioner level.