🏫 Data Science Center, Tredtin Hall, Monday, Wednesday & Friday | 11:30–12:20
🕥 Mondays 2:30–4:30
🕥 Tuesdays 1:30–2:30
📆 By appointment, sign up or email amber.camp@chaminade.edu
💻 I strongly recommend attending office hours for any of the following:
- Troubleshooting code
- Chatting about the theory behind the code
- Help building your personal website in R
- Chatting about opportunities in data science
Install R, RStudio, and Git
Follow the installation guide before our first class. Stop before the "How to accept and submit assignments" section (don't do anything below that section).
| Week | Module | Assignment Due |
|---|---|---|
| 8/25–8/29 | Syllabus, Course Logistics & Technology Prep | Assignment 1 (9/1) |
| 9/1–9/5 | Complete Installation & RStudio Demo | Assignment 2 (9/5 at 11:30am) |
| 9/8–9/12 | Importing & Cleaning Data, Missing Values | |
| 9/15–9/19 | Transforming Data (tidyverse, dplyr, joins) | Assignment 3 (9/21) |
| 9/22–9/26 | EDA & Descriptive Statistics | Assignment 4 (9/28) |
| 9/29–10/3 | tidycensus & GitHub Collaboration | Assignment 5 (10/5) |
| 10/6–10/10 | Analytics Practice, Reshaping Data | Assignment 6 (10/12) |
| 10/13–10/17 | Monday holiday, Catch-up Week | |
| 10/20–10/24 | Personal Websites using R & Quarto | Assignment 7 (10/26) |
| 10/27–10/31 | flexdashboard | Assignment 8 (11/2) |
| 11/3–11/7 | Wind-down & Special Topics | Assignment 9 (11/9) |
| 11/10–11/14 | Final Project Prep, Special Topics | Project proposal (11/16) |
| 11/17–11/21 | Work on Final Projects | |
| 11/24–11/28 | Work on Final Projects ( Wed & Fri no class) | |
| 12/1–12/5 | Final Presentations | |
| 12/8–12/12 | Final Project Materials Due Thursday, 12/11 at 5:30pm |
Finished early? Want to explore more?
Check out our Stretch Menu for optional challenges and ideas to deepen your learning all semester long.
- 💻 Coding practice: try solving problems multiple ways, write your own functions, and explore new R tools
- 📊 Visualization challenges: make new plots, customize themes, or go beyond the plots we are doing in class (e.g.,
plotly) - 🧰 Package exploration: install and try packages beyond class (e.g.,
lubridateorstringr) - 🔗 Git/GitHub power moves: write better commit messages, try branching, open issues or pull requests
- 🤝 Community engagement: help your neighbor, share datasets or code snippets, or demo your solution in class
- 🧠 Data curiosity: explore new datasets, calculate new statistics, write mini-reports
- 🏆 Going beyond: create dashboards or Quarto websites, contribute to open source, or connect what you learn to your major
These are optional but highly encouraged!
Use them to practice, get creative, and challenge yourself while helping make our class more collaborative.