Provides a theoretical and practical introduction to modern techniques for the analysis of large-scale, heterogeneous data. Covers key concepts in inferential statistics, supervised and unsupervised machine learning, and network analysis. Teaches functional, procedural and statistical programming techniques for working with real-world data. Prerequisite: IMT 573.