Merge pull request #11 from ryanlovett/main

Remove "here" hyperlinks.

README.md

@@ -32,8 +32,7 @@ For added security, you can choose to enter a passphrase during key creation.
 This is optional.
 
 ### Windows
-If you're running Windows, please install either [WSL2 native linux](https://learn.microsoft.com/en-us/windows/wsl/install) 
-or [gitbash](https://www.git-scm.com/download/win).
+If you're running Windows, please install either [WSL2 native linux](https://learn.microsoft.com/en-us/windows/wsl/install) or [gitbash](https://www.git-scm.com/download/win).
 
 Open a terminal, and run the following command.  WSL2 is preferred, but there
 are a few additional steps required.
@@ -45,9 +44,7 @@ For added security, you can choose to enter a passphrase during key creation.
 This is optional.
 
 ### Upload your public ssh key to GitHub
-Please follow the instructions [here](https://docs.github.com/en/authentication/connecting-to-github-with-ssh/adding-a-new-ssh-key-to-your-github-account) 
-to upload your SSH public key to GitHub.  This allows you to authenticate while
-using `git` in a repo.
+Please follow [the instructions](https://docs.github.com/en/authentication/connecting-to-github-with-ssh/adding-a-new-ssh-key-to-your-github-account) to upload your SSH public key to GitHub. This allows you to authenticate while using `git` in a repo.
 
 ## Setting up your fork and clones
 
@@ -168,8 +165,9 @@ and there should be a big green button on the top that says `Compare and pull re
 Click on that, check out the commits and file diffs, edit the title and
 description if needed and then click `Create pull request`.
 
-Once you create a pull request, a github action will run which will build the jupyterbook
-and publish it to https://ds-modules.github.io/curriculum-guide/intro.html as a public facing 
+Once you create a pull request, a github action will run which will build the
+jupyterbook and publish it to
+https://ds-modules.github.io/curriculum-guide/intro.html as a public facing
 website. Github action will fail if there are issues with the commit.
 
 # Recommended reading

faq/onboarding.md

@@ -25,14 +25,14 @@
 
 **GitHub Issues:** The best way for instructional staff to request help with the DataHub is through filing an issue using the [GitHub templates](https://github.com/berkeley-dsep-infra/datahub/issues/new/choose).
 
-**Slack Channel:** If you have anything you'd like to discuss with w/the infra team, please join the Slack channel. Access [uctech.slack.com](http://uctech.slack.com/) (anyone with a berkeley.edu account can get in) and join the #ucb-datahubs channel to interact with the infra team. 
+**Slack Channel:** If you have anything you'd like to discuss with w/the infra team, please join the Slack channel. Access [uctech.slack.com](http://uctech.slack.com/) (anyone with a berkeley.edu account can get in) and join the #ucb-datahubs channel to interact with the infra team.
 
 **DataHub Service Lead:** In addition, you can reach out to Balaji Alwar <[email protected]> directly if there are time-sensitive issues.
 
 ##### DataHub - Common Requests 
 **Packages:** Please test your assignments for hub compatibility before the start of the semester. Check whether all the needed Python/R packages and their required versions are installed. If not, please use the [package request template](https://github.com/berkeley-dsep-infra/datahub/issues/new?assignees=felder%2Cbalajialg&labels=package-request&template=package_request.yml&title=Request+python+package+X+for+class+Y) to raise a request to the infra team.  The Infra team requires at least 2 business days for a turnaround on support requests such as this.
 
-**Elevated Privilege Access:** You can use this [GitHub template](https://github.com/berkeley-dsep-infra/datahub/issues/new?assignees=balajialg&labels=support&template=admin_request.yml) to request [elevated privileges](https://ds-modules.github.io/curriculum-guide/faq/admin.html?highlight=admin) for course staff to troubleshoot student servers in the requested hub. 
+**Elevated Privilege Access:** You can use this [GitHub template](https://github.com/berkeley-dsep-infra/datahub/issues/new?assignees=balajialg&labels=support&template=admin_request.yml) to request [elevated privileges](https://ds-modules.github.io/curriculum-guide/faq/admin.html?highlight=admin) for course staff to troubleshoot student servers in the requested hub.
 
 **Big Assignments / High Use times:** You can share the important date(s)/time(s) for workshops/exams/assignments etc. when you expect the resource requirement to be greater than usual. We will review your request and get back to you directly about the feasibility of increasing resources. You can provide us with all the relevant information using the [calendar event scheduling template](https://github.com/berkeley-dsep-infra/datahub/issues/new?assignees=felder%2Cbalajialg&labels=support&template=resourcescheduler.yml&title=Increase+compute+resources+for+Course+XXX+between+specific+date%28s%29%2Ftime%28s%29).
 
@@ -46,7 +46,7 @@ Finally, provide us with any feedback that will help us improve our hub operatio
 
 **How can I learn more about DataHub to onboard myself?**
 
-- If you are new to DataHub and want to know more, checkout [here](https://datahub.berkeley.edu/hub/login?next=%2Fhub%2F). 
+- If you are new to DataHub and want to know more, [try logging in](https://datahub.berkeley.edu).
 
 - If you are interested in learning more about the configuration of various Berkeley hubs, you can checkout [UC Berkeley's JupyterHubs documentation](https://docs.datahub.berkeley.edu/en/latest/).
 
@@ -64,7 +64,7 @@ We have 15+ hubs which cater to the diverse needs of the campus audience. We hav
 
 [DataHub](https://datahub.berkeley.edu/) has a memory of 1 GB, which should meet the teaching/research needs of most of our users. If you are interested to know more about the memory consumption in your instance, Please follow the steps below,
 
-- Look at the top right corner of your Python/R notebook for the term memory. It will highlight the amount of memory you had consumed against the total memory available for your server. 
+- Look at the top right corner of your Python/R notebook for the term memory. It will highlight the amount of memory you had consumed against the total memory available for your server.
 - If your consumed memory is greater than the available memory for your instance then your server will crash resulting in you either optimizing your workflow to be less compute intensive or requesting additional RAM,
 
 ```{figure} ../images/memory.png
@@ -118,10 +118,10 @@ If these templates are not exhaustive enough to cover the type of issue you are
 
 **As an instructor what do I need to do to set up the hub for my course?**
 
-Honestly, nothing! You are free to use the DataHub starting today. 
+Honestly, nothing! You are free to use the DataHub starting today.
 
 ```{note}
-We expect that all course members log in using their UC Berkeley email id. We also expect that you are using [DataHub Link Generator](https://chromewebstore.google.com/detail/datahub-link-a/ijbgangngghdanhcnaliiobbiffocahf?hl=en) to distribute materials to your class. We can also help with setting up the links. 
+We expect that all course members log in using their UC Berkeley email id. We also expect that you are using [DataHub Link Generator](https://chromewebstore.google.com/detail/datahub-link-a/ijbgangngghdanhcnaliiobbiffocahf?hl=en) to distribute materials to your class. We can also help with setting up the links.
 ```
 
 **What instructions should I share with students at the start of the semester**
@@ -140,7 +140,7 @@ We can’t allow non UC Berkeley users as our authentication system only allows
 **How do my students download their submissions as a PDF?**
 We recommend that you use the following options,
 
-- **For Jupyter Notebooks:** Select File -> Download as -> WebPDF to download the PDF version of your notebook. 
+- **For Jupyter Notebooks:** Select File -> Download as -> WebPDF to download the PDF version of your notebook.
 ```{figure} ../images/downloadhtml.PNG
 :width: 500px
 :align: center

faq/share.md

@@ -15,8 +15,8 @@ We are always interested in getting case studies of how different teaching teams
 
 - [Data science modules](https://ds-modules.github.io/) are short explorations into data science that give students the opportunity to work hands-on with a data set relevant to their course and receive some instruction on the principles of data analysis, statistics, and computing. Here is the [link](https://github.com/ds-modules) to DS-Modules repository which has information on the many courses using it at Berkeley. Reach out to Eric Van Dusen (ericvd@berkeley) if you want help to make notebooks.
 
-- Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. If you are interested to learn more about this autograding software then check this link [here](https://otter-grader.readthedocs.io/en/latest/). 
+- Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. If you are interested to learn more about this autograding software then see [Otter Grader's documentation](https://otter-grader.readthedocs.io/en/latest/).
 
-- If you are interested to learn more about the conversations by the Jupyter Hub community, then check the discourse [link](https://discourse.jupyter.org/)
+- If you are interested to learn more about the conversations by the Jupyter Hub community, then check [Jupyter's discourse site](https://discourse.jupyter.org/).
 
 - If you are thinking about setting up a JupyterHub distribution for a small number of users (around 100) on a single server, then check out [The Littlest JupyterHub](https://tljh.jupyter.org/en/latest/)

faq/troubleshoot.md

@@ -190,9 +190,9 @@ If you got this error after running this command mentioned below, this is most l
 grader.export(pdf=False, force_save=True)
 ```
 
-In the long term, you should plan to rewrite your existing test cases to suit the new format and then run the latest version of otter grader in your notebooks. If you need further support with rewriting test cases then please reach out to the otter team [here](https://github.com/ucbds-infra/otter-grader/issues/new?assignees=&labels=question&template=information-request.md&title=).
+In the long term, you should plan to rewrite your existing test cases to suit the new format and then run the latest version of otter grader in your notebooks. If you need further support with rewriting test cases then please [reach out to the otter team](https://github.com/ucbds-infra/otter-grader/issues/new?assignees=&labels=question&template=information-request.md&title=).
 
 
 **What should I do if I have an issue that has not been documented in the FAQ?**
 
-Raise a github [issue](https://github.com/berkeley-dsep-infra/datahub/issues/new/choose) or reach out to Balaji Alwar([email protected])! We will keep adding common issues to this FAQ document!
+Raise a github [issue](https://github.com/berkeley-dsep-infra/datahub/issues/new/choose) or reach out to Balaji Alwar([email protected])! We will keep adding common issues to this FAQ document!

module/general/what-is-a-module.md

@@ -1,13 +1,11 @@
 # What is a Data Science Module?
 
-A Data Science Module is a short exploration of data science designed to fit into an existing course. Modules give non-data-science students the opportunity to explore data-driven methods in familiar domains.
+A [Data Scient Module](https://ds-modules.github.io/DS-Modules/) is a short exploration of data science designed to fit into an existing course. Modules give non-data-science students the opportunity to explore data-driven methods in familiar domains.
 
 Each module is designed by a team of CDSS curriculum developers, working closely with the course instructor, and may be taught by either the CDSS team or the instructors themselves.
 
 <!-- add modules textbook link instead below? -->
 
-An overview page is available [here](https://ds-modules.github.io/DS-Modules/).
-
 ![](../../assets/modules.jpg)
 
 ### Prerequisites

technology/connectortools-module.md

@@ -10,9 +10,4 @@ The `connectortools` module contains many useful tools that can be used to teach
 
 ## Code
 
-The code can be found \[here\]\([https://github.com/data-8/connector-instructors/tree/gh-pages/connectortools\](https://github.com/data-8/connector-instructors/tree/gh-pages/connectortools%29\).
-
-## Examples
-
-Examples of how the code can be used are \[here\]\([https://github.com/data-8/connector-instructors/tree/gh-pages/examples\](https://github.com/data-8/connector-instructors/tree/gh-pages/examples%29\).
-
+See the [source code](https://github.com/data-8/connector-instructors/tree/gh-pages/connectortools), and [examples](https://github.com/data-8/connector-instructors/tree/gh-pages/examples) of how the code can be used.

technology/jupyter/jupyter-notebooks.md

@@ -2,4 +2,4 @@
 
 ## What are Jupyter Notebooks?
 
-Jupyter notebooks are a tool used for in-browser computing that allow you to include code, text, and visualizations on the same page. Once created, these notebooks can be distributed to students and then downloaded in various formats for submission. You can see an example of a Data 8 notebook [here](http://datahub.berkeley.edu/user-redirect/interact?repo=data8assets&path=materials/sp17/lab/lab01\). The link might take some time to download all of the files. Once you see a page of many files, click on the file called `lab01.ipynb`. This is the Jupyter notebook assignment.
+Jupyter notebooks are a tool used for in-browser computing that allow you to include code, text, and visualizations on the same page. Once created, these notebooks can be distributed to students and then downloaded in various formats for submission. View [an example](http://datahub.berkeley.edu/user-redirect/interact?repo=data8assets&path=materials/sp17/lab/lab01\) of a Data 8 notebook. The link might take some time to download all of the files. Once you see a page of many files, click on the file called `lab01.ipynb`. This is the Jupyter notebook assignment.

technology/quarto.md

@@ -1,17 +1,13 @@
 # Using Quarto in DataHub
 
-Quarto is an open-source publishing system that is particularly valuable for instructors who want to create dynamic, interactive course materials. Whether you're developing lecture notes, assignments, or entire textbooks, Quarto provides a powerful, flexible platform that integrates code, data, and narrative, making it ideal for educational settings. It supports a variety of programming languages, including R, Python, Julia, and Observable JavaScript, enabling instructors to design course content that actively engages students through hands-on coding exercises and real-time data analysis.
+[Quarto](https://quarto.org) is an open-source publishing system that is particularly valuable for instructors who want to create dynamic, interactive course materials. Whether you're developing lecture notes, assignments, or entire textbooks, Quarto provides a powerful, flexible platform that integrates code, data, and narrative, making it ideal for educational settings. It supports a variety of programming languages, including R, Python, Julia, and Observable JavaScript, enabling instructors to design course content that actively engages students through hands-on coding exercises and real-time data analysis.
 
 ```{figure} ../images/Quarto.gif
 :width: 500px
 :align: center
 :name: Convert R markdown assignments/labs with quarto to produce pdfs
 ```
 
-```{note}
-For more information about Quarto, Read [here](https://quarto.org/)
-```
-
 ### Opportunities to Integrate Quarto in Your Workflow
 
 ##### 1. Creating Interactive Lecture Notes
@@ -49,27 +45,15 @@ Eg: Stat 20 instructor Andrew Bray uses Quarto to generate stat20.org. Quarto is
 
 Quarto integrates with popular Integrated Development Environments (IDEs) such as RStudio, VSCode and JupyterLab. You can visit [this website](https://quarto.org/docs/get-started/) to learn more about the detailss.
 
-**RSudio:** In RStudio, you can create, edit, and render Quarto documents (.qmd files) directly.
-
-```{note}
- Read more about it [here](https://quarto.org/docs/get-started/hello/rstudio.html)
-```
-
-**Jupyter:** In JupyterLab, you cannot create/edit Quarto documents but can convert Jupyter notebooks to various formats using Quarto's command-line tools.
-
-```{note}
- Read more about it [here](https://quarto.org/docs/get-started/hello/jupyter.html)
-```
+**RSudio:** You can create, edit, and render Quarto documents (.qmd files) directly [in RStudio](https://quarto.org/docs/get-started/hello/rstudio.html).
 
-**VSCode:** Check whether VSCode and [VSCode Quarto extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto) is enabled in your hub. If yes, you can render and preview quarto documents and can have syntax highlighting in addition to command line tools to convert to varied documents. 
+**Jupyter:** You cannot create/edit Quarto documents [in JupyterLab](https://quarto.org/docs/get-started/hello/jupyter.html), but you can convert Jupyter notebooks to various formats using Quarto's command-line tools.
 
-```{note}
- Read more about it [here](https://quarto.org/docs/get-started/hello/vscode.html)
-```
+**VSCode:** If VSCode and [VSCode Quarto extension](https://marketplace.visualstudio.com/items?itemName=quarto.quarto) are enabled in your hub, you can [use them](https://quarto.org/docs/get-started/hello/vscode.html) to render and preview quarto documents with syntax highlighting. You can also use command line tools to convert to varied documents.
 
 ### Workflow for Beginner Instructors
 
-Imagine you’re preparing a lecture on data visualization. You start by writing your notes in a simple Markdown file (.qmd), adding a few basic code examples that generate charts. You then use Quarto to render these notes as a PDF handout and an HTML page for your course website. 
+Imagine you’re preparing a lecture on data visualization. You start by writing your notes in a simple Markdown file (.qmd), adding a few basic code examples that generate charts. You then use Quarto to render these notes as a PDF handout and an HTML page for your course website.
 
 ### Steps to Convert Documents to HTML/PDF via Quarto
 
@@ -113,4 +97,4 @@ Typst is a modern typesetting system designed to provide a user-friendly alterna
 quarto render my-document.qmd --to pdf
 ```
 
-The above command converts your Quarto Markdown (. qmd) into a PDF.
+The above command converts your Quarto Markdown (. qmd) into a PDF.

technology/resources.md

@@ -4,5 +4,5 @@ Students taking a course with a data science component may need extra resources
 
 ### Laptop Lending
 
-- Students who need access to a computer can borrow a Chromebook from Moffitt Library for the entire semester. You can read more about this program [here](https://cdss.berkeley.edu/academics/undergraduate-programs/data-science-chromebooks-program).
-- The Student Technology Equity Program (STEP)(https://studenttech.berkeley.edu/step) provides need-based loans of technology hardware to graduate, professional and undergraduate students at UC Berkeley.
+- Students who need access to a computer can [borrow a Chromebook from Moffitt Library](https://cdss.berkeley.edu/academics/undergraduate-programs/data-science-chromebooks-program) for the entire semester.
+- The Student Technology Equity Program (STEP)(https://studenttech.berkeley.edu/step) provides need-based loans of technology hardware to graduate, professional and undergraduate students at UC Berkeley.