Generated by claude-sonnet-4-6 · 2026-06-21 03:18 · grounding rag
Model Answer
(i) Data Exploration:
It is the stage in the AI Project Cycle where the collected data is visually represented using graphs, charts, databases, maps, etc., to identify and interpret the patterns present in the data.
(ii) Data Features:
Data features are the specific attributes or characteristics of the data that are relevant to the problem being solved. They are the parameters selected from the dataset to train the AI model.
Source: Chapter 1, Section 1.1 – AI Project Cycle
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Explanation
- The question has two sub-parts worth 1 mark each, so keep each definition to 1–2 lines.
- Data Exploration links to the step where raw acquired data is visualised to find patterns — mention visualisation tools (graphs, charts, etc.) for full marks.
- Data Features relates to selecting relevant attributes/parameters from data — examiners expect the word "attributes" or "parameters."
- Both definitions must be in the context of the AI Project Cycle, not general ML/statistics definitions.