Description

Welcome to CS109! Learning from data in order to gain useful predictions and insights. This course introduces methods for five key facets of an investigation: data wrangling, cleaning, and sampling to get a suitable data set; data management to be able to access big data quickly and reliably; exploratory data analysis to generate hypotheses and intuition; prediction based on statistical methods such as regression and classification; and communication of results through visualization, stories, and interpretable summaries.

We will be using Python for all programming assignments and projects.

The course is also listed as AC209, STAT121, and E-109.

General Information

Course website
cs109.github.io/2014

Announcements

Announcements are not public for this course.
Staff Office Hours
NameOffice Hours
jacob dorabialski
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Steve Klosterman
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Lane Erickson
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M Lackner
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Joy
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Korey Nathaniel Tucker
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Rick Lee
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Antonia Miruna Oprescu
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Marcus Way
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Verena Kaynig-Fittkau
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nurul zaman
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Olivia Angiuli
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Tarik Adnan Moon
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Alex D'Amour
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Brian Feeny
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Tudor Giurgica-Tiron
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Felix Gonda
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Zhijie Zhou
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Angela Fan
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Michael Packer
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Diana Miao
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Amy
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Logan Kerr
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Stephanie Hicks
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Rafael Irizarry
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Yang
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Mingxiang Teng
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Claudio Rosenberg
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