AI Project Cycle Quiz

Define Data Exploration and state one reason why it is important in the AI Project Cycle.

List any TWO common data‑visualization charts suitable for categorical data, as mentioned in the handbook.

Differentiate between a Rule‑Based and a Learning‑Based modelling approach (one point each).

Explain what is meant by overfitting in model evaluation.

Using the forest‑fire example, describe *True Positive* and *False Negative* cases.

State any TWO key steps involved in deploying an AI model.

Why is it NOT recommended to evaluate a model using the same data on which it was trained?

Give ONE example from the handbook where AI deployment benefited society and name the domain.

What role does the *Data Acquisition* stage play before moving to Data Exploration?

Provide TWO reasons why continuous monitoring is essential after deployment of an AI model.