In this course, ad click prediction means using customer data to build a classification model that estimates whether someone is likely to click an advertisement. The focus is on learning the connected steps around that prediction task, not just producing a single model output.

You would use this kind of workflow when you want to estimate a yes-or-no customer action from existing data instead of relying only on judgment or summary charts. In the course, it is treated as a repeatable way to prepare data, train classifiers, and judge how useful the predictions are.

It sits in the build-and-test phase of a machine learning project, after you have data to work with and before predictions are used to support later decisions. This course emphasizes connecting preparation, modeling, and evaluation so the work forms one coherent process.