This course overviews machine learning and its importance for data science. It also provides students with theory and implementation of state-of-the-art machine learning algorithms for large-scale real-world applications. Topics include supervised learning (regression, classification). Accuracy computation alternatives, feature selection and reduction, optimization of classifiers, cross-validation will be covered.