4.1 Explain AI’s Role in Exploratory Data Analysis (EDA) AI-TECHNICAL-PRACTITIONER Practice Questions (Page 1)

Questions 1–5

1. 1application · medium

   An analyst is working with a high-dimensional dataset containing many correlated features. The goal is to reduce dimensionality while retaining the most relevant information for a classification task. Which AI-based EDA technique is most appropriate?

   • AFeature importance ranking to select the top features most predictive of the target class.
   • BGenerating a heatmap of all pairwise correlations and manually removing features with high correlation.
   • CVisualizing the data with a scatter plot of the first two columns.
   • DClustering the data to find natural groups, regardless of the target variable.
   Reveal Solution Discussion Select an answer first
2. 2foundation · easy

   In exploratory data analysis (EDA), which task is most directly automated by AI techniques?

   • AWriting the final research report for stakeholders
   • BDeciding the business question without human input
   • CManually reviewing each row of data to ensure accuracy
   • DAutomatically detecting and correcting inconsistent data entries
   Reveal Solution Discussion Select an answer first
4. 3application · medium

   A data analyst uses an AI tool that suggests a strong correlation between two variables in a dataset. Before acting on this finding, what should the analyst do?

   • AValidate the correlation with domain knowledge and additional statistical tests.
   • BIgnore the finding because AI is always biased.
   • CAccept the correlation as causal and implement changes immediately.
   • DAsk the AI tool to automatically implement a policy change based on the correlation.
   Reveal Solution Discussion Select an answer first
5. 4foundation · easy

   What does AI-driven data profiling primarily provide?

   • AA summary of data distributions, data types, and anomalies
   • BA final predictive model ready for deployment
   • CA list of all possible hypotheses to test
   • DA complete data governance policy
   Reveal Solution Discussion Select an answer first
6. 5expert · hard

   A data scientist is exploring a dataset with many variables and uses an AI tool to discover patterns. The tool identifies a cluster of data points that seems unusual. The scientist needs to decide whether this cluster is a genuine pattern or an artifact of noise. What is the most appropriate approach?

   • AInvestigate the cluster further by examining the underlying data points and using domain knowledge.
   • BTreat the cluster as a genuine pattern and build a model around it immediately.
   • CAsk the AI tool to automatically remove the cluster from the dataset.
   • DIgnore the cluster because AI is prone to finding false patterns.
   Reveal Solution Discussion Select an answer first