Designing and Realising
This is where your analysis becomes a working system: a trained model, the pipeline and service that carry it, and the interface someone actually uses, built and validated together with stakeholders rather than alone at your desk.
Starting Points
- Data transformation pipeline — Data Engineering and Preparation
- Experiment Tracking Logs — Machine Learning Model Engineering
- Model Cards — Machine Learning Model Engineering
- Model Training Scripts — Machine Learning Model Engineering
- API endpoints — Deployment and Maintenance
- Client Interface — Deployment and Maintenance
- System Architecture Diagram — Deployment and Maintenance
- Data Quality Test Suite — Data Engineering and Preparation
- Monitoring and Maintenance Plan — Deployment and Maintenance
Level 2 Learning Outcome Designing & Realising
You design and realise solutions in consultation with stakeholders, work according to provided methods, and validate whether the solution works as intended. Success criteria:
- You work from a concrete plan or design, and you can explain what you are going to make, why you choose that, and which steps are involved
- You explore what already exists in the field and apply relevant standards and methods
- You actively involve stakeholders by showing work in a timely manner and processing feedback
- You validate the solution before delivering it, demonstrate that it works as intended, is free from known errors and ready for use
- You take into account the interests of end users, such as privacy, security or accessibility
Level 3 Learning Outcome Designing & Realising
You design and realise solutions in consultation with stakeholders, work according to professional standards and systematically validate whether the solution works and meets the needs. Success criteria:
- You design and realise in a planned manner, justify choices in relation to alternatives and adapt based on new insights
- You independently select relevant standards and methods from the professional field and substantiate why these fit the context
- You proactively involve multiple stakeholders with differing interests, coordinate systematically and consciously weigh their feedback in your decisions
- You systematically validate whether the solution does what it is supposed to do, critically evaluate its quality and draw conclusions for improvement
- In your design and realisation, you consciously take into account the broader impact on end users and society, forming your own ethical judgement