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Data Science & AI

Statistics, machine learning fundamentals, AI ethics, and data-driven decision making.

About this event

Data Science & AI tests the fundamentals of working with data and modern AI systems. Expect questions on descriptive and inferential statistics, the data science workflow (collection, cleaning, modeling, evaluation), core machine learning concepts (supervised vs. unsupervised learning, overfitting, training/test splits), how large language models and generative AI work at a conceptual level, and AI ethics topics like bias, privacy, and misinformation.

Test day

What to expect

60 minutes, 100 questions

You have 60 minutes to answer 100 multiple-choice questions. Each question has four options (A, B, C, D) with exactly one correct answer. There is no penalty for wrong answers -- always fill in your best guess.

Computer-graded, instant results

Tests are machine-scored. Questions are drawn from the official FBLA topic outline for this event, distributed proportionally across all topic areas. Expect a mix of recall (definitions, formulas), application (scenario-based), and analysis questions.

Top scorers advance

The highest-scoring competitors at each regional advance to the state competition. State winners compete at the National Leadership Conference (NLC). Study the official FBLA topic outline -- it lists the exact subject areas and their approximate weight on the test.

What's on the test

Descriptive & inferential statisticsData science workflowMachine learning fundamentalsSupervised vs. unsupervised learningNeural networks & deep learning basicsGenerative AI & large language modelsAI bias & ethicsData privacy & governance

Study resources

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