– Anaconda and modules of Python; how to upload users’ transactions and aggregate the data – Behavior of anomalous users, how to check for outliers with the help of multivariate normality test – Data analysis with various tests usage – Clustering algorithms (k-means, dbscan), dimensionality reduction (t-sne, PCA) and other methods of unsupervised learning – Interpretation of results and visualization