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Final Exam :Generative AI: Enhance your Data Analytics Career (IBM Data Analyst Professional Certificate) Answers 2025

1. Question 1

Most accurate application of generative AI in data analytics:

  • ❌ Filling missing data

  • ❌ Musical compositions

  • ❌ Image creation

  • Generating coherent and context-appropriate text

Explanation:
In analytics, GenAI is mainly used for NLP tasks such as insights summarization.


2. Question 2

How data analysts use GenAI for testing/development:

  • Augment their datasets using synthetic data

  • ❌ Game environments

  • ❌ Simple text

  • ❌ Medical images


3. Question 3

GenAI tool for creating face recognition datasets:

  • ❌ DataWrangler

  • ❌ Tableau

  • ❌ RapidMiner

  • Nvidia’s StyleGAN2


4. Question 4

Secure infrastructure for LLMs + data governance:

  • ❌ Facebook Insights

  • ❌ AiDIN

  • ❌ DataRobot

  • Palantir Artificial Intelligence Platform


5. Question 5

Tool using data augmentation for ML model improvement:

  • ❌ Haptik

  • ❌ Facebook Insights

  • DataRobot

  • ❌ Palantir AIP


6. Question 6

How GenAI enhances extraction of insights:

  • Identifying hidden patterns and correlations

  • ❌ Natural language queries

  • ❌ Anomaly detection

  • ❌ Narratives


7. Question 7

GenAI enhancement for data preparation:

  • ❌ Hypothesis generation

  • ❌ Storytelling

  • ❌ Natural language queries

  • Identifying and correcting outliers


8. Question 8

Definition of data augmentation:

  • Artificially increasing dataset size by modifying existing data

  • ❌ Generating stories

  • ❌ Converting text to images

  • ❌ Creating charts


9. Question 9

GenAI tool to augment structured data:

  • ❌ Imagen

  • ❌ BigGAN

  • CTGAN

  • ❌ StyleGAN2


10. Question 10

Prompt to generate:

SELECT AVG(AGE) FROM Boston_house_price

  • ❌ Find age…

  • ❌ What is the age…

  • ❌ Update average age…

  • What is the average age in Boston data set?


11. Question 11

Tool to augment image datasets with realistic high-resolution images:

  • ❌ GauGAN

  • ❌ Imagen

  • ❌ CTGAN

  • StyleGAN2


12. Question 12

Feature analyzing all pairs of attributes:

  • ❌ Describe

  • ❌ Multivariate

  • ❌ Univariate

  • Bivariate

(Pair plots are bivariate: two variables at a time)


13. Question 13

Visualization to verify outliers:

  • ❌ Annotation

  • ❌ Histograms

  • ❌ Color coding

  • Generate box plots


14. Question 14

Prompt generating:

SELECT COUNT(*) FROM Boston_house_prices

  • ❌ Sum of rows

  • ❌ Total sum of prices

  • What is the count of rows?

  • ❌ Count of columns


15. Question 15

Embeddable analytics conversational chat service:

  • ❌ Tableau Pulse

  • ❌ Crystal

  • ThoughtSpot Sage

  • ❌ Analytics Chatbot


16. Question 16

Model consideration technique improving interpretability:

  • ❌ Imaging data

  • ❌ Perpetuate biases

  • ❌ Manipulative inputs

  • Feature attribution


17. Question 17

Organizational challenge with GenAI:

  • ❌ Continuous learning

  • ❌ Data quality

  • ❌ Risk aversion

  • Change management


18. Question 18

Python-based interactive dashboard tool with LLM integration:

  • Dash

  • ❌ ThoughtSpot

  • ❌ Akkio

  • ❌ Tableau AI


19. Question 19

Storytelling aspect explaining relevance to goals:

  • Contextualization

  • ❌ Logical organization

  • ❌ Anecdote

  • ❌ Visualization


20. Question 20

Copilot feature enabling correlations & new Excel formulas:

  • ❌ Model generation

  • ❌ Drafting

  • ❌ Presentation creation

  • Natural language queries


🧾 Summary Table

Q Correct Answer
1 Generating coherent text
2 Synthetic data augmentation
3 StyleGAN2
4 Palantir AIP
5 DataRobot
6 Hidden patterns & correlations
7 Correcting outliers
8 Artificial dataset expansion
9 CTGAN
10 “What is the average age…”
11 StyleGAN2
12 Bivariate
13 Box plots
14 “What is the count of rows?”
15 ThoughtSpot Sage
16 Feature attribution
17 Change management
18 Dash
19 Contextualization
20 Natural language queries