Course modules
The data chain
- Collection, quality, transformation: the least visible and most decisive part.
- Data architectures: lake, warehouse, lakehouse and what each is for.
Applied machine learning
- Framing a problem as a model, and choosing the metric.
- Training, honest evaluation, and the traps of data leakage.
Production and MLOps
- Deployment, monitoring, data drift and retraining.
- Reproducibility and experiment traceability.
Generative AI
- Large language models: capabilities, limits, costs.
- Retrieval-augmented generation, evaluation, guardrails.
Governance and compliance
- Explainability, bias, decision traceability.
- The regulatory framework and documentation obligations.
Why Altodia
- Practitioner trainers — our instructors design and operate these systems daily for our clients. They teach what they practise.
- Hands-on approach — exercises, case studies and real projects so that what is covered can be applied immediately.
- Complete resources — access to a library of guides, tutorials and tooling that stays useful after the course.
- Professional network — exchanges with practitioners in the field and with the other participants.
Our learners retain more of what they learn by doing it, report improved professional performance, and say the content helped them directly in their careers.
What you take away
A model carried end to end during the course, from raw dataset through to supervised deployment, with the documentation that goes with it.
