Data-Science-202-ISU

Lectures

August

08/21 Lecture 0

08/23 Lecture 1-1

08/23 Lecture 1-2

08/28 Lecture 1-3-R installation

08/28 Lecture 1-4-Rstudio Rmarkdown

08/28 Lecture 1-5

08/30 Lecture 1-6-Git

September

09/04 Lecture 2-1-R basics

09/06 Lecture 2-2-R graphics I

09/11 Lecture 2-3-R graphics II

09/18 Lecture 2-4-R logical

09/20 Lecture 2-5-R factors

09/25 Lecture 2-6-R factors visual

October

10/02 Lecture 3-1-dplyr

10/02 Lecture 3-2-dplyr example 1

10/04 Lecture 3-3-dplyr example 2

10/04 Lecture 3-4-dplyr example 3

10/09 Lecture 3-5-tidyr-messy I

10/16 Lecture 3-6-tidyr-messy II

10/18 Lecture 3-7-messy III

10/23 Lecture 3-8-messy IV

10/23 Lecture 3-9-messy V

10/30 Lecture 4-1-time

November

11/01 Lecture 4-2-time series

11/01 Lecture 4-3-layers

11/13 Lecture 4-4-maps

11/15 Lecture 5-1-polishing

11/27 Lecture 6-1-web scraping I

11/29 Lecture 6-2-web scraping II

11/29 Lecture 7-1-image processing

December

12/26 Presentation

Labs

08/30 Lab 1

09/13 Lab 2

09/27 Lab 3

10/11 Lab 4

10/25 Lab 5

11/08 Lab 6

Homework

08/28 Homework 1 (due 09/04)

09/06 Homework 2 (due 09/13)

09/20 Homework 3 (due 09/28)

10/05 Homework 4 (due 10/16)

10/21 Homework 5 (due 10/30)

11/15 Homework 6 (due 11/27)

Sample exam

10/23 Sample exam

10/23 Sample exam solution

Exam (11/06)

Acknowledgement

Most of the materials of this course are from Dr. Heike Hofmann at ISU. The instructor greatly appreciates Dr. Hofmann shares the notes, examples, ect., which help preparing the course.