6.439[J] Statistics, Computation and Applications (New)

Class Info

Hands-on analysis of data demonstrates the interplay between statistics and computation. Includes four modules, each centered on a specific data set, and introduced by a domain expert. Provides instruction in specific, relevant analysis methods and corresponding algorithmic aspects. Potential modules may include medical data, gene regulation, social networks, finance data (time series), traffic, transportation, weather forecasting, policy, or industrial web applications. Projects address a large-scale data analysis question. Students taking graduate version complete additional assignments. Limited enrollment; priority to Statistics and Data Science minors and to juniors and seniors.

This class has 6.01, 6.0002, 18.03, 18.06, 2.087, 6.008, 6.041B, 14.30, 16.09, and 18.05 as prerequisites.

6.439[J] will not be offered this semester. It will be instructed by S. Jegelka and C. Uhler.

This class counts for a total of 12 credits. This is a graduate-level class.

You can find more information on MIT OpenCourseWare at the Algorithms for Inference site.

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