MTH 190

Source code to generate the course webpage for Holyoke Community College HCC 190: Introduction to Data Science https://nics-github.github.io/MTH_190/. Most of the content is in either:

• _quarto.yml: Set theme of webpage along with links in navigational bar.
• index.qmd: A single Moodle-style page that lists all announcements and lectures notes in reverse-chronological order.
• PS.qmd: All problem sets/homeworks.
• projects.qmd: Details on the mini-projects and term project.
• syllabus.qmd: Course info/description, topics, materials, evaluation, and expectations.

How to build this webpage

This webpage is built/compiled using R Markdown Websites. To compile this webpage for yourself, do the following:

1. Get the contents of this directory/repository:
   • If you are not familiar with GitHub, click the green "Clone or download" button on the top-right -> Download ZIP -> Unzip SDS192-master.zip.
   • If you are familiar with GitHub, clone this repository.
2. Double-click the SDS192.Rproj to open RStudio.
3. If you haven't already, install the following R packages:
   • rmarkdown and devtools
   • At the top of index.Rmd: all CRAN R packages listed .
   • At the top of index.Rmd: the emo and patchwork packages must be installed from GitHub using the devtools::install_github() function.
4. Go to the "Build" pane of RStudio -> More -> Configure Build Tools... -> Ensure that "Project build tools" is set to "Webpage".
5. Click "Build Website".
6. The website will display in the Viewer pane. The resulting index.html file and all other files for the webpage will be saved in the docs/ folder.

How to publish this webpage

To publish/deploy this webpage and make it viewable on the web, you need to either:

1. Copy the contents of the docs/ folder to your personal webpage or whatever domain hosting service you use.
2. Use GitHub pages as I do. RStudio's R Markdown Websites page gives instructions on how.

Credit

The format for this site was borrowed from Albert Kim's SDS 192 course

If not created by me or referred to in some other way the activities and projects for this course are from:

• The above mentioned website
• Data Science in a box.
• Ben Baumer's SDS 192 course page