Glossary
Data Scientist Terms & Vocabulary
15 essential data scientist terms with plain-English definitions: the vocabulary you’ll hear in training and on day one.
Key data scientist vocabulary
These 15 terms come up constantly in data scientist training, on the job and in interviews. Knowing them helps you follow instructions, document accurately and sound prepared.
- A/B test
- An experiment comparing two versions.
- Bias
- Systematic error in data or models.
- Classification
- A model that predicts categories.
- Cross-validation
- Testing model performance on different data splits.
- Dashboard
- A visual display of key metrics.
- Data cleaning
- Fixing errors and gaps in data.
- Dataset
- A collection of data.
- Feature
- An input variable used in a model.
- Machine learning
- Algorithms that learn from data.
- Model
- A mathematical representation used to make predictions.
- Overfitting
- When a model learns noise instead of patterns.
- P-value
- A measure used in hypothesis testing.
- Regression
- A model that predicts numbers.
- SQL
- A language for querying databases.
- Training data
- Data used to build a model.
Practice these terms
Test yourself with the free Data Scientist practice test: it includes vocabulary questions built from this list. For a complete course, see Data Scientist training.
Browse terms from every career in our career glossary.