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11 - 12 of 12 results for: CS161

IMMUNOL 207: Essential Methods in Computational and Systems Immunology

Introduction to the major underpinnings of systems immunology: first principles of development of computational approaches to immunological questions and research; details of the algorithms and statistical principles underlying commonly used tools; aspects of study design and analysis of data sets. Prerequisites: CS106a and CS161 strongly recommended.
Terms: Spr | Units: 3

MS&E 334: Topics in Social Data

This course provides a in-depth survey of methods research for the analysis of large-scale social and behavioral data. There will be a particular focus on recent developments in discrete choice theory and preference learning. Connections will be made to graph-theoretic investigations common in the study of social networks. Topics will include random utility models, item-response theory, rank aggregation, centrality and ranking on graphs, and random graphs. The course is intended for Ph.D. students, but masters students interested in research topics are welcome. Recommended: 221, 226, CS161, or equivalents.
Last offered: Autumn 2018
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