Cornell University
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Computational Methods for Information Science Research

INFO 6010

INFO 6010: Computional Methods For Information Science Research

Computation is an essential tool for many facets of information science research. Examples of its utility include capture, access and analysis of digital data; visualization of that data for analysis, interpretation and information extraction; construction of user-focused applications; and analysis of textual and sensor-derived information to detect patterns and dynamics of human activities, social interactions and social networks. Effective use of computation requires a mixture of skills including structuring data, accessing data, programming, choosing and applying computational analysis methods, and designing visualizations. This course covers the mixture of these skills with the goal of providing information science graduate and masters students with the appreciation of their utility and the ability to employ them in future research. The course is project-based, allowing students to understand the use of computational methods to pursue research interests.

Prerequisites: Graduate standing. Basic programming experience (at the level of CS1110 or CS1112 or INFO1100, including variables, arrays, strings, loops, conditionals, methods and functions, basic recursion, file IO, object-oriented design, debugging), plus introductory-level background in probability and statistics. Prior knowledge of Python is not required. This course will not teach programming per se, but rather the use of computational methods and tools for data-oriented research tasks.

Note: This course draws both from Physics 7682 / CIS 6229 ("Computational Methods for Nonlinear Systems") and from the former Info 6307 ("Learning from Web Data", which it replaces).