Test description
The test checks knowledge of machine learning for data scientists at a medium level, whose skills are up-to-date with the most common algorithms and techniques.
Questions include outputs used for interpretation. The test focuses on the main subjects related to machine learning, testing subjects such as supervised learning, unsupervised learning, feature engineering, hypothesis testing and decision-making in terms of accuracy.
Topics: clustering, dimensionality reduction, regression, classification, accuracy, text analysis, time series analysis.