About the Course
See the syllabus for details. The course is divided into three rough parts,
- Core data science coding skills
- Modeling
- Advanced topics
Course Material
Date | Lecture | Slides | Tutorial |
---|---|---|---|
Aug. 19 | Welcome | Slides | |
Data Visualization | Slides | Tutorial 01(.rmd) | |
Aug. 24 | RMarkdown I | Slides | |
Aug. 26 | RMarkdown II | Tutorial 02 sol(.zip) | |
Aug. 31 | Data Transformation I | Slides | Lecture 04 |
Sep. 2 | Data Transformation II | Slides | Tutorial 03 sol(.rmd) |
Sep. 7 | Final Project Instruction | Slides | |
Data Transformation III | Tutorial 04 sol(.zip) | ||
Sep. 9 | Data Import | Slides | |
Sep. 14 | Project Proposal Discussion | ||
Sep. 16 | Project Proposal Discussion | ||
Sep. 21 | Exploratory Data Analysis | Slides | |
Sep. 23 | Tidy Data | Slides | Tutorial 06 sol(.rmd) |
Sep. 28 | Joins | Slides | Lecture 10 |
Sep. 30 | Factors | Slides | |
Oct. 5 | Programming I | Slides | Tutorial 09 sol(.rmd) |
Tutorial 10 sol(.rmd) | |||
Oct. 7 | Programming II | Slides | |
Oct. 12 | University Day (No Class) | ||
Oct. 14 | Programming III | Slides | |
Oct. 19 | Modeling I | Slides | |
Oct. 21 | Fall Break | ||
Oct. 26 | Modeling II | Slides | Tutorial 11 sol(.zip) |
Tutorial 12 sol(.zip) | |||
Oct. 28 | Modeling III | Slides | Tutorial 13 sol(.zip) |
Nov. 2 | Modeling IV | Slides | |
Nov. 4 | Modeling V | Slides | |
Nov. 9 | Modeling VI | Slides | Tutorial 14 sol(.rmd) |
Nov. 11 | Modeling VII | Slides | Tutorial 15 sol(.rmd) |
Nov. 16 | Intro to Deep Learning | ||
Nov. 18 | Final Presentation | ||
Nov. 23 | Final Presentation | ||
Nov. 25 | Thanksgiving | ||
Nov. 30 | Final Presentation |
Homework Tracker
All homework assignments are to be submitted via Sakai.
Date assigned | Instructions | Solutions | Due Date (Time) |
---|---|---|---|
Aug 19 | HW1(.rmd) | Aug 29 (11:55 PM) | |
Aug 29 | HW2(.rmd) | Sep 12 (11:55 PM) | |
Sep 7 | A1(.zip) | Sep 19 (11:55 PM) | |
Sep 19 | HW3(.rmd) | Sep 28 (11:55 PM) | |
Sep 26 | HW4(.rmd) | Oct 3 (11:55 PM) | |
Oct 3 | A2(.zip) | Oct 10 (11:55 PM) | |
Oct 10 | HW5(.rmd) | Oct 17(11:55 PM) | |
Oct 17 | A3(.zip) | Oct 31 (11:55 PM) | |
Oct 31 | HW6(.rmd) | Nov 7 (11:55 PM) | |
Nov 7 | HW7(.rmd) | Nov 14 (11:55 PM) | |
Nov 14 | A4(.zip) | Nov 28 (11:55 PM) | |
Final Project Details
For the final project, each section of STOR 320 will be divided
(ideally) into research groups of size 5. To ensure fairness, students
will be assigned randomly based on the sample
function in
R.
Research Group Assignments
To find your research group, see the spreadsheet sponsored by Google.
Four Roles
Although everyone is responsible for the entire project, each member of the group will be assigned a specific role for accountability and consistency. These four specific roles are described as follows:
The Creator: Meet with Instructor to Propose Your Group’s Research Idea, Lead Designer in Slides
The Interpreter: Schedule and Meet with Instructor or Instructional Assistant to Share Findings from Exploratory Analysis, Evaluate Practice Presentation
The Orator(s): Give a Captivating 5-7 Minute Slideshow Presentation During the Last Three Lectures
The Deliverer: Deliver Your Group from Evil by Editing and Submitting the Exploratory Analysis and Final Report via Sakai Before the Deadline
Four Parts Including Point Values
This final project will be divided into four parts worth a total of 100 points. Each part will have a clear rubric as non-subjective as possible. The parts along with total point values are found below:
- P1: Project Proposal (10 Points)
- P2: Exploratory Data Analysis (20 Points)
- P3: Final Written Paper (40 Points)
- P4: Final Presentation (30 Points)
Due Dates of Individual Parts
Part | Description | Method of Submission | Due Date (Time) |
---|---|---|---|
P1 | Project Proposal | Sakai | Sep 13 (11:55PM) |
Proposal Meeting | Class | Sep 14 / Sep 16 (2:00PM-3:15PM) | |
P2 | Exploratory Data Analysis | Sakai | Oct 22 (11:55PM) |
EDA Meeting | Lab | Week of Oct 25 to Oct 29 | |
P3 | Final Report | Sakai | Nov 30 (11:55PM) |
P4 | Presentation Slides | Sakai | Nov 17 /Nov 22 / Nov 29 (11:55PM) |
Final Presentation | Class | Nov 18 /Nov 23 / Nov 30 (2:00PM-3:15PM) | |
Above Average Final Projects from Previous Courses
Class Participation Record
To find your class participation record, see the spreadsheet sponsored by Google.
Acknowledgements
Thanks to Dr. Mario and Dr. Characiejus for sharing their course materials.
Reading
R for Data Science (R4DS)
R Programming for Data Science (RP4DS)
Text Mining with R (TMwR)
The Art of R Programming (AoRP)
ModernDive (MD)
Additional resources
This page was last updated on 2024-05-01 16:08:40 Eastern Time.