Email: [email protected]
Class Time: TR, 2:40 - 4:25 PM in Harney 430
Office Hours: TR, 1:20 - 2:20 PM in Harney 107B (James Wilson's Office)
Book: R for Data Science by Hadley Wickham and Garret Grolemund
Syllabus: Link
By the end of this course, you will be able to
- Proficiently wrangle, manipulate, and explore data using the R programming language
- Use contemporary R libraries including ggplot2, tibble, tidyr, dplyr, knitr, and stringr
- Visualize, present, and communicate trends in a variety of data types
- Communicate results using R markdown and R Shiny
- Formulate data-driven hypotheses using exploratory data analysis and introductory model building techniques
The focus of this course will be to provide you with the basic techniques available for making informed, data-driven decisions using the R programming language. This is not a statistics course, but will provide you the intuition to make hypotheses about complex questions through visualization, wrangling, manipulation, and exploration of data. The course will be graded based on the following components:
- Attendence (20%): Attendance will be recorded and you will lose points for every class you miss.
- Assignments (40%): You will be assigned a computational assignment to be completed using RStudio and the package knitr regularly throughout class.
- Case Studies (20%): You will be assigned applied case studies throughout the class that are to be completed using RStudio.
- Final Project (20%): The final project will be a computational case study that brings together the techniques learned throughout the semester. The description for this project will be provided towards the mid point of the semester.
I will do my best to keep this schedule accurate and up to date. However, I reserve the right to change it as I deem necessary. Usually this will be due to the amount of material we are able to cover in class.
If you wish to view the notes I use during lecture you can see them here, though note I often change these based on class questions.
Introduction
| Topic | Reading | Assignment | Due Date | In Class Code |
|---|---|---|---|---|
| Introduction - History of Data Science | Ch. 1 What is Data Science? | HW 1 | Thursday, 8/23 | Installing R, RStudio, and LaTeX |
| R and RStudio | HW 2 | Tuesday, 8/28 | In Class Code 2018-08-23 | |
| R Packages and RMarkdown | HW 3 | Tuesday, 9/4 | In Class Activity In Class Activity Solution: Rmd Code In Class Activity Solution: PDF Output Class Code - Packages Class Code - R File to PDF Class Output - R File to PDF Class Code - Rmd File to PDF Class Output - Rmd File to PDF Class Activity 2 |
Data Structures in R
Ethics in Data Science
| Topic | Reading | Assignment | Due Date | In Class Code |
|---|---|---|---|---|
| Ethics in Data Science |
Data Wrangling and Plotting
Programming
| Topic | Reading | Assignment | Due Date | In Class Code |
|---|---|---|---|---|
| Control Flow | Ch. 21 in R for Data Science | HW 8 | Tuesday 11/27 | Class Code 181113 |
| Writing Functions | Ch. 19 in R for Data Science | Function Lab - Rmd Function Lab - PDF Class Code 181127 Class Code 181129 |
Other
| Topic | Reading | Assignment | Due Date | In Class Code |
|---|---|---|---|---|
| Extra Review |
| Example |
|---|
| Song Lyrics |
| Case Study | Data | In-Class Date | Due Date | Notes |
|---|---|---|---|---|
| CS 1 | Ramen Reviews | September 25th, 2018 | October 9th, 2018 | Case Study 1 Notes |
| CS 2 | hour data day data |
October 23, 2018 | November 8, 2018 |
| Description | Due Date | Notes |
|---|---|---|
| Project Sign-Up will be through a google doc link on Canvas | November 1st at 9 AM | |
| Final Project Description - UPDATED due to smoke | December 7 at 11:59 PM | Final Tips and Tricks Report Tips Presentation Tips |
- Monday, August 27th - Last day to add the class
- Friday, September 7th - Census date. Last day to withdraw with tuition reversal
- Tuesday, October 16th - Fall break! (no class)
- Friday, November 2nd - Last day to withdraw
- Thursday, November 22nd - Thanksgiving Holiday (no class)
- Thursday, December 7 - Final Projects Due
- Tuesday, December 4th - Last day of class
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent