Join a focused course at DataNowKurs that walks you through a complete workflow: data ingestion, transformation, model training, validation, deployment and monitoring. Each session centers on a practical case with artifacts you can reuse.
Hands-on labs modeled on real business workflows
Scenarios tested for operational readiness
Practical clarifications and examples
How are the course cases selected?
Cases are chosen for practical relevance: we analyse common workflow patterns across management, retail and manufacturing and design condensed scenarios that highlight decision points. Each case includes data, a clear success criterion, and variant paths to explore activity-offs between latency, accuracy and maintainability.
What level of tooling knowledge is required?
Courses assume familiarity with basic data concepts and at least one programming language used in data workflows. We provide tool-agnostic patterns and optional labs for popular stacks so participants can apply lessons with their existing tools.
How do projects move from lab to production?
Modules include practical readiness steps: validation checklists, monitoring scenarios and playbooks for rollback and incident response. These are framed as reproducible examples so teams can adapt them to their deployment environments.
Choose the level of support and case depth that fits your team
Access a selection of introductory scenario labs and community forum threads to evaluate the teaching approach.
Guided learning with mentor reviews and assessed scenario projects. Intended for practitioners moving workflows toward production readiness.
Structured program focused on real-world data engineering, ML pipeline orchestration and production AI practices. Includes hands-on labs, scenario-based projects and instructor feedback tailored for Swiss and EU compliance contexts.