Data Science & AI – Full Interactive Practice Quiz & Flashcards

📊 Data Science & AI – Full Practice Quiz (All Topics)

This expanded quiz covers all FBLA Data Science & AI knowledge areas. Answer all questions, then scroll down for flashcards.

Probability & Statistics Foundations

1. Which measure is least affected by outliers?

2. Variance measures:

3. A normal distribution is:

4. Expected value represents:

5. Which is a continuous variable?

Data Analysis & Statistics for AI

6. Best chart to show relationship between two numeric variables?

7. Boxplots are useful for identifying:

8. Logistic regression is used when output is:

9. Data cleaning improves:

10. K-means is an example of:

Tools for Data & AI

11. Which SQL clause filters rows?

12. Pandas is primarily used for:

13. NumPy specializes in:

14. Relational databases store data in:

AI Basics

15. Generative AI is designed to:

16. A major limitation of generative AI is:

17. NLP focuses on:

18. LLMs are trained mainly on:

Machine Learning

19. Which dataset is used for final evaluation?

20. Unsupervised learning uses:

21. Deep learning relies on:

Perception, Representation & Reasoning

22. Predicate logic is:

23. Bayesian networks represent:

Privacy, Ethics & Data Literacy

24. Algorithmic bias often comes from:

25. Hallucinations refer to:

26. Structured data is:

27. Binary numbers use base:

28. Data wrangling involves:


🧠 Flashcards – Key Concepts

Mean
Average of values
Median
Middle value
Variance
Measure of spread
Normal Distribution
Symmetric bell curve
Scatterplot
Shows correlation
Data Cleaning
Improves data quality
Pandas
Python data analysis library
NumPy
Numerical computing
Generative AI
Creates new content
LLM
Large Language Model
Supervised Learning
Labeled data
Unsupervised Learning
No labels
Deep Learning
Multi-layer neural networks
Predicate Logic
Rule-based reasoning
Bayesian Network
Probabilistic graph
Algorithmic Bias
Bias from data/models
Structured Data
Rows and columns
Data Science Process
Collect → Clean → Analyze → Model → Evaluate → Deploy