A lecture series on explainable artificial intelligence — built for practitioners who need to understand, justify, and audit the systems they deploy.
The program runs across eight sequential modules, each building directly on the last. Expect roughly four to six hours per module — split between lecture content, worked examples, and a short written reflection. There is no live attendance requirement.
Access is structured, not open-ended. Each module unlocks after the previous one is marked complete, which keeps the material in sequence and prevents gaps from forming.
Pre-recorded lectures with annotated slides, downloadable as PDF. No live sessions.
Eight modules. Most learners finish within nine to twelve weeks at a measured pace.
Module reflections and a final case study. No timed exams, no pass-or-fail pressure.
This program works best for people who already have some exposure to machine learning — enough to have encountered a model output and wondered what produced it.
You do not need a research background. You do need patience with technical reading and a willingness to sit with incomplete understanding before it resolves.
Three practitioners who have each spent years working at the intersection of model development and accountability.
Curriculum Lead — Interpretability Methods
Dagmar spent six years at a financial services firm where regulatory auditors required written justification for every automated credit decision. She built the LIME and SHAP modules from that experience directly.
Applied ML — Model Auditing
Radovan has contributed to three open-source XAI toolkits and led internal audit processes for deployed models in a healthcare logistics context. His modules focus on what happens after deployment.
AI Ethics — Accountability Frameworks
Nneka's background spans policy research and technical implementation. She designed the final module on communicating model behaviour to regulators and non-technical decision-makers.
The SHAP module changed how I write model documentation. I had been describing outputs — now I describe reasoning.
— Petra Kuznetsová, data analyst, Windsor ON
Completion certificate issued on final case study submission — includes module breakdown for portfolio use.
All lectures, slides, and written materials are in English. Adapted for Canadian educational context.
Twelve months of access from enrolment date. Download slides and worked notebooks at any point.
Modules are reviewed annually. Learners enrolled in the current cohort receive updates at no additional cost.