About CS 187 A

Basic data science techniques, from import to cleaning to visualizing and modeling, using the R language. Machine learning methods include regression, classification and clustering algorithms. Programming methods include user-defined functions. Prerequisite: STAT 111 or STAT 141 or STAT 143 or STAT 211. Cross-listed with: STAT 187.

Notes

Prereqs enforced by the system: STAT 111 or STAT 141 or STAT 143 or STAT 211 Open to Degree and CDE students; Cross listed with STAT 187 A; Total combined enrollment: 50

Section Description

Basic data science techniques, from import to cleaning to visualizing and modeling, using the R language. Machine learning methods include regression, classification and clustering algorithms. Programming methods include user-defined functions.

Section Expectation

At the end of the course, students will be expected to know how to construct the appropriate visuals for data using the GGplot2 package, manipulate data frames using base R and the Tidyverse packages, write custom functions, perform loops, and build/improve models using machine learning techniques. No programming experience required.

Evaluation

Students will be assessed by homeworks, in-class quizzes, and a group project.

Course Dates

to

Location

L/L Commons 216 (View Campus Map)

Times

to on Tuesday and Thursday

Important Dates

Note: These dates may change before registration begins.

Note: These dates may not be accurate for select courses during the Summer Session.

Deadlines
Last Day to Add
Last Day to Drop
Last Day to Withdraw with 50% Refund
Last Day to Withdraw with 25% Refund
Last Day to Withdraw

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