Introduction to scalable computing paradigms suitable for data-intensive analytics, with a focus on abstractions, algorithms, and infrastructure for scaling data science, machine learning, and data engineering tasks using multiple machines. The concepts will be applied through a substantial, practical project involving collecting, manipulating, and analyzing large datasets, and discussing findings through scientific reports. Prerequisites: CMPUT 200, 201, 204, and 291, and one of CMPUT 191 or 195.