Merge pull request #74 from ds-modules/fix

Adding resources for students

_toc.yml

@@ -127,6 +127,8 @@ parts:
   chapters:
   - file: technology/resources
     title: Resources for Students
+  - file: technology/troubleshooting_tips_students
+    title: Troubleshooting Tips for Students
 - caption: Workshop Resources
   chapters:
   - file: technology/instructor-activity

technology/resources.md

@@ -2,37 +2,7 @@
 
 Students taking a course with a data science component may need extra resources in order to be successful. In this section, we provide information and links to connect students with computers and in-person help.
 
-### Semester-Long Laptop Lending \(Connectors\)
+### Laptop Lending
 
-Connector course classrooms do NOT have computers for student use. Students who need access to a computer can borrow a Chromebook from Moffitt Library for the semester. You can read more about this program [here](https://data.berkeley.edu/news/data-science-students-can-borrow-laptops-semester).
-
-To check the availability of laptops at the current time:
-
-1. Go to [http://oskicat.berkeley.edu/search/r](http://oskicat.berkeley.edu/search/r)
-2. Search for "CS C8"
-3. Scroll down to the see the list; individual laptops are marked either AVAILABLE or otherwise
-
-To borrow a Chromebook, can go to the circulation desk at Moffitt Library. Students must present proof of course registration. For more details, please see [this page](https://data.berkeley.edu/news/data-science-students-can-borrow-laptops-semester), also linked above.
-
-**Note on using external software:** Chromebooks will not support software that must be downloaded and installed. Therefore, using such external software is not recommended.
-
-### Short-term Laptop Lending \(Modules\)
-
-The library has MacBook Air laptops \(running OSX or Windows\) available for short-term checkout to any undergraduate or graduate student with a valid Cal ID or yellow library card. Loan periods and locations are as follows:
-
-* 4 hour loans:  Engineering Library, Social Research Library, Moffitt Library
-* 1 day loans:  Bioscience Library, Social Research Library
-* 14 day loans:  Moffitt Library
-
-  All laptops are available on a first-come, first-served basis and cannot be reserved ahead of time. For more information on laptop lending and restrictions, please see the library's [Electronic Devices Lending Policy](http://www.lib.berkeley.edu/using-the-libraries/laptop-lending) and [Frequently Asked Questions](http://www.lib.berkeley.edu/about/faq?faq_category=239).
-
-You can check the availability of laptops using the links below:
-
-* [MacBook Air with OSX](http://oskicat.berkeley.edu/record=b21338181~S1)
-* [MacBook Air with Windows](http://oskicat.berkeley.edu/record=b21338184~S1)
-
-Library devices use Deep Freeze to restrict data from being saved to the hard drive, meaning that **all work and downloaded software will be deleted** when the device is shut down. Students must save any work to a cloud-based service \(like datahub\) or an external drive.
-
-### Office Hours: Data Peers
-
-The Data Peers program hosts drop-in office hours and other data science support for Berkeley students. Data Peers are students affiliated with data science courses or clubs. They can assist students with troubleshooting code and understanding a wide range of data science topics, including statistics, web scraping, visualization, and more. Students can find Data Peers on the 1st floor of Moffitt Library. Hours and consulting topics are available at [https://data.berkeley.edu/education/datapeers](https://data.berkeley.edu/education/datapeers).
+- 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.

technology/troubleshooting_tips_students.md

@@ -0,0 +1,79 @@
+# Troubleshooting Tips to Use Datahub
+
+## About the UC Berkeley DataHub:  
+
+The DataHub is UC Berkeley’s implementation of Jupyterhub and is a free service made available to UC Berkeley students to provide a small amount of computing and storage on a virtual machine running in the cloud. This guide provides an overview of the tasks you will need to complete before the semester begins, during the semester, and at the end of the semester. This high-level information will help you navigate your coursework effectively using the UC Berkeley DataHub.
+
+#### Before the Semester Begins
+
+
+##### 1. Browser and Internet Check
+Browser Compatibility: Ensure you are using a compatible web browser (Chrome, Firefox, Safari) that is updated to the latest version.
+Internet Connection: Verify you have a stable internet connection to access DataHub smoothly. 
+
+##### 2. Account Setup and Access
+Activate CalNet ID: Ensure your CalNet ID is activated and functioning properly.
+Access DataHub: Go to datahub.berkeley.edu and log in with your CalNet ID to verify you can access the platform. ( and allow Bcourses to authenticate “DataHub is requesting access to your account”.) 
+
+##### 3. Familiarize Yourself with DataHub
+Overview: Review student resources to understand the varied features of DataHub.
+Interface Tour: Explore the DataHub interface, including the JupyterLab and RStudio environments.
+
+#### During the Semester
+
+##### 1. Accessing Course Materials
+Course Hub: Use nbgitpuller links shared by your course instructors to launch notebooks in DataHub
+Notebooks and Scripts: Open and work on Jupyter Notebooks, R scripts, or other files as provided by your instructor.
+To manage files in JupyterHub:
+To upload a file, click the "Upload" button in the JupyterHub interface and select the file from your local machine.
+To download a file, right-click on the file in the JupyterHub interface and select the "Download" option.
+
+##### 2. Completing Assignments
+Regular Use: Regularly log in to DataHub to complete assignments, run analyses, and work on projects.
+Save Work: Save your progress frequently. It's good practice to manually save your work as well.
+Check Storage Space: Delete unnecessary files and constantly check the storage size of the home directory.  You can do this by opening a Terminal, and executing du -sh
+Don’t Duplicate Shared Directory Content: If your course work requires shared directories where instructors are storing large datasets, don’t create a copy of the files in your home directory. Always, read data from the shared directory.
+Do Your Work in Sub Directories: Create a sub directory for each assignment and do your work there. Avoid working on assignments from the root directory as they may lead to data issues if done wrongly.
+
+##### 3. Collaboration and Sharing
+Note: Datahub doesn’t have collaboration tools at this time as we are continuously testing the latest updates.
+Instructor Feedback: Share your work with instructors or TAs for feedback by downloading and submitting your notebooks as required.
+
+##### 4. Troubleshooting
+###### Restart Kernel/Server: Try restarting your kernel as a classic troubleshooting step to see if the error goes away. If the problem persists, restart your server.
+
+###### Kill Process: Having too many things open on Datahub can cause issues. To check running processes and kill them follow instructions in Curriculum Guide
+
+** UI Based Approach: **
+- In Notebook - click Jupyter Icon in UR to get to ”tree” 
+- In “tree” click running processes tab
+- Right click on any process to kill it ( or Kill all). In Lab you can see running processes in tab on left with this icon
+
+** CLI approach: **
+- Open the terminal in Datahub.
+- Use the command ps aux to list all running processes.
+- Find the process ID (PID) of the processes you want to stop.
+- Use the command kill <PID> to terminate those processes.
+- Repeat these steps as necessary to manage your system resources.
+
+Support: Reach out to course TAs for technical help, and they will contact infrastructure staff if they are unable to resolve your issue.
+
+What if I can’t access DataHub?
+Ensure your CalNet ID is active and try logging in again. If the problem persists, inform your TA or check out this guide for additional help.
+How do I install additional packages?
+Use !pip install package-name in a Jupyter Notebook cell for Python packages, or install.packages("package-name") in the R console.
+
+
+Can I use DataHub off-campus?
+Yes, you can access DataHub from anywhere with an internet connection.
+What should I do if I encounter a technical issue?
+First, try restarting your kernel. If the issue persists, contact your course TA,  and if they can’t resolve it they will reach out to DataHub staff.
+
+#### End of the Semester
+##### 1. Backup Your Work
+Backup coursework: Back up your notebooks and data to either your personal device or an external storage service like Google Drive, Dropbox.
+User Home Directory Archiving: Files unused for 90 days will be archived and stored in a low cost storage. You will need to open a request with the DataHub team to retrieve your unused files.
+##### 2. Clean Up Your Workspace
+Clean Up: Clean up your DataHub workspace by deleting unnecessary files and folders.
+Feedback: Provide feedback on your experience with the DataHub team to help improve the service for future students.
+Additional Resources