The stakeholders of a machine learning model have confirmed that they understand the objective and...

The ML workflow typically involves iterative steps, beginning with data preparation once the model and framework are selected. The syllabus explains:

"The steps shown in Figure 1 (the ML workflow) do not include the integration of the ML model with the non-ML parts of the overall system. Typically, ML models cannot be deployed in isolation and need to be integrated with the non-ML parts... The next step would be data preparation as part of the ML workflow to provide input data to support training by an ML algorithm or prediction by an ML model."

(Reference: ISTQB CT-AI Syllabus v1.0, Sections 3.2 & 4.1)