Machine Learning Foundations
The end-to-end machine learning workflow with hands-on model building. Deliberately heavy on evaluation and failure modes, because that is where organisations lose money.
Who it is for
Analysts, developers, technical product managers and data-adjacent professionals who need real understanding of how ML models are built and evaluated.
What the course covers
- The ML landscape: supervised, unsupervised and where each applies
- Framing a business problem as an ML problem, and knowing when not to
- Feature engineering and data preparation
- Building and training core models: regression, classification, clustering
- Evaluation done properly: the right metric, train-test discipline, avoiding overfitting
- Model interpretation, fairness testing and explaining a model to a business stakeholder
- From notebook to production: what actually has to happen next
Frequently asked questions
Who is Machine Learning Foundations for?
Analysts, developers, technical product managers and data-adjacent professionals who need real understanding of how ML models are built and evaluated.
How is the course delivered?
As a live, instructor-led private cohort for your team: 1 day(s), online by default, on site by arrangement, tailored to your industry and tools.
How is it priced?
Per engagement rather than per seat, based on group size, customisation and delivery mode. Tell us your team and goals and you get a written proposal, usually within one business day.
Looking for a certified AI foundation? ICP-FAI, Foundations of AI is the ICAgile-certified companion to every course here. For a phased organisation-wide programme, see the Enterprise AI Readiness Programme, or watch real class feedback from our cohorts.