A typical AI project life-cycle generally includes six main steps: problem definition, data gathering, data preparation, model building, evaluation and refinements, and deployment.
Data gathering is the process of collecting relevant data for the problem.
Evaluation & Refinements involve testing the model’s performance and improving it.
Deployment means putting the model into production for real-world use.
Data cleaning is not generally listed as a separate step because it is part of the larger data preparation phase.
In practice, data cleaning is an activity done within data preparation to remove errors, handle missing values, and ensure high-quality data.
Therefore, while important, data cleaning is not counted as one of the six main steps on its own.
So, the correct answer is option (B) Data cleaning.