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Graphs have become a central part of a growing number of applications with large societal impact, such as social networks, recommendation systems, fraud detection, and national security. This course will explore the processing of such graphs, especially ones that can grow to large scale size. The course format will be to spend approximately 2 weeks on each of a half dozen relevant modules, where in each module an introduction to the subject will be followed by individual talks by each student on different aspects or variants of that topic, and submission of a short report. Feedback from the class will be provided to each student on each talk, to help improve their presentation skills. An initial module will cover the mathematical definition of graphs, their common representation as data structures, and key algorithms. Follow-on modules will cover key applications and data sets that have relevance, graph-oriented programming languages, and parallel graph algorithms. In addition, each student will also be expected to write and demonstrate at the end of the semester a graph processing program, ideally relevant to their particular research. Grading will be based on timely submission and presentation of all materials, and evaluation by the instructor of the written reports.