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Learn Enterprise AI, earn certificates with free online courses from Stanford, University of Michigan, Coursera, The University of British Columbia and other top universities around the world. Read reviews to decide if a class is right for you.
Apply generative AI to business challenges: create content, personalize customer experiences, automate tasks, and strengthen branding alongside AI and machine learning fundamentals.
Run a full FP&A cycle for a simulated insurer: select KPIs and drivers, build a driver-based model, run variances and AI-assisted forecasts, and assemble an executive narrative pack.
Apply generative AI to business problems: prompt large language models for marketing content, personalize customer touchpoints, turn unstructured data into insights, and set ethical guardrails.
Apply generative AI to leadership: use prompt patterns and in-context learning for decision-making, leadership transitions, HR conversations, scenario planning, risk management, and ethical concerns.
Explore how generative AI reshapes business and work: industry impacts, new business opportunities, adoption readiness, emerging job roles, and hands-on labs and projects.
Evaluate agentic AI transformation as an executive: assess agentic workflow architectures, outcome-based pricing, procurement interoperability, workforce orchestration incentives, and frontier risks like agentic drift.
Apply generative AI to business tasks across marketing, finance, operations and HR: write dependable prompts, build no-code Zapier automations, govern AI risks, and make an adoption business case.
Take AI out of the chat window and into your department: apply Generative AI across marketing, finance, HR, and knowledge workflows with Copilot, Notion AI, and NotebookLM.
Build enterprise AI solutions with H2O GPTe: AI-powered search, advanced RAG techniques, LLM agents, Python API automation, and AI-driven web apps in H2O Wave.
Put AI to work as an executive tool: draft communications, run SWOT and scenario planning, configure custom MyGPTs, and build Notion AI knowledge systems.
Lead AI adoption without being a technologist: learn how generative AI works, apply prompt patterns, and use the A-C-H-I-E-V-E model to prioritize opportunities responsibly.
Design generative AI integration patterns: batch metadata extraction from 10-K reports, document summarization, real-time intent classification, RAG architectures, and responsible AI practices for production LLM deployments.
Move from using AI to leading its adoption: build GenAI roadmaps in Miro AI and Notion AI, set governance policies with Claude, and pitch board-level business cases.
Implement application integration patterns and AI-assisted development tools to enhance enterprise systems and build generative AI applications.
Turn AI outputs into actionable insights, build stakeholder trust through transparency, address black-box explainability, and align AI strategy and use cases with enterprise goals.
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