Working with Generative AI for Organizations

Dates

November 16-19, 2026

Length of Course

4 days

9 AM - 4 PM (ET)

Prerequisites

None

Delivery Method

Live Online

Cost

$1,850 CAD

Cost includes a non-refundable $50 registration fee

Instructor

Mark-Humphries-PS800

Mark Humphries

Professor, Wilfrid Laurier University

Course Summary

Generative AI has moved from novelty to infrastructure faster than any technology in living memory and the gap between what frontier systems can do and what most professionals know how to do with them is widening by the month. This four-day intensive course is designed to close that gap. Built for working professionals and policymakers, it pairs a clear, jargon-free account of how large language models actually work with extensive hands-on practice. Participants progress from writing effective prompts to designing reliable, multi-step workflows and supervising AI “agents” that can carry out real tasks. Throughout, we confront the myriad issues posed by generative AI, including hallucination, bias, data security, interpretability, and the ethical and governance questions every organization now faces, so that participants leave able to use these tools critically, productively, and responsibly. The course is taught by a working researcher who builds AI systems daily, using current frontier models and real use-cases drawn from policy, administration, analysis, and communications.

Learning Outcomes

By the end of this course, participants will be able to:

  • Explain, in plain language, how large language models, reasoning models, and AI agents work and why they succeed and fail in specific ways.
  • Design and refine prompts and multi-step workflows that produce reliable, verifiable results for research, analysis, writing, and decision-support tasks.
  • Evaluate and select among frontier tools (ChatGPT, Claude, Gemini, and others) for a given task, weighing capability, cost, and risk.
  • Identify and mitigate the practical risks of generative AI, including hallucination, bias, data security, copyright, and the limits of interpretability.
  • Build a concrete plan for integrating generative AI into their own work and organization, with appropriate guardrails and verification practices.

Covered in this Course

  • A short history of AI and how we arrived at the “ChatGPT surprise”
  • How LLMs really work: training, embeddings, inference, reasoning, and emergent capabilities
  • From chatbots to agents: tool use, automation, and the accelerating capability curve
  • Prompting, context, and workflow design (hands-on)
  • Working with your own documents and data, plus verification and benchmarking
  • Reliability, hallucination, bias, interpretability, and the “black box” problem
  • Ethics, copyright, data security, and AI governance
  • The knowledge-work transition: what AI means for jobs, skills, and organizations
AI for Corporations PS1200

Instructor

Mark-Humphries-PS800

Mark Humphries

Professor, Wilfrid Laurier University

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