Resources & Getting Help


datascience Library Documentation Link

Jupyter Notebook

We will use Jupyter Notebooks to code in this class that are hosted by OIT. Go to the container manager and look for “JupyterLab with Pytorch for Data Science and Machine Learning”. Click on the button to reserve your instance of the notebook. Once your instance is reserved you can click on “Pytorch” among your reserved containers, start the server, and upload any necessary files. We recommend you create a folder per notebook.

Later in the class, if you want to install and run Jupyter Notebooks locally, we will update this page with instructions.


We will be using Gradescope to submit labs and projects. If you are unfamiliar with Gradescope or aren’t sure how to submit your assignment, they created a Gradescope help document for you.

Getting Help

There are many sources and opportunities for help in this class. Because of the flipped classroom model, there is ample time to receive help in class from your peers and the teaching team. We also will have a class forum with 24/7 access. Finally, the teaching team will hold in-person or virtual office hours outside of class where you can receive help one-on-one or as a group.

Office Hours

Starting the week of 8/30. Virtual offices will use the same Zoom link as the class’s Zoom.

  • Sunday: Leah 7-9 pm ET (virtual, see link in Sakai’s Overview page)
  • Monday: Prof. KSM 12-1 pm ET (virtual, see link in Sakai’s Overview page)
  • Thursday:
    • Prof. KSM 11:30-12:30 (right after class) in her office (LSRC D224)
    • David 12:30-1:30 pm ET (virtual, see link in Sakai’s Overview page)
  • Friday:
    • Eric 2-4 pm ET (virtual, see link in Sakai’s Overview page)
    • David 4-5 pm ET (virtual, see link in Sakai’s Overview page)

Asking Questions Asynchronously

  1. DO be respectful and patient. This means not only in the text of your interactions with each other but also in using other features, for example, you could like a post to show it was useful.
  2. DO check if your question has already been asked or answered. If it has already been asked but not answered, star or watch it so you can find it later.
  3. DO NOT post a portion of your code and ask someone to fix it. Instead, follow the guidelines for posting about code on the forum below.

How to post about code on the class forum

We are very happy when we see students utilizing the forum to ask questions. However, in order to make the platform more efficient, we have these guidelines before posting about code. It is not only for our benefit but also for yours!

  1. If you are getting an error that you do not understand, go backward through the output to find the first time it references your code. Read the code there carefully, considering the error output. Is there a mistake in the code at or near that line? Always try to debug on your own before asking for help. While we are more than happy to help, solving a problem on your own is great practice.
  2. Search the forum to see if a similar question has been asked.
  3. Decide if you can ask your question in a generic way such that you do not need to include your code in the post. If you can, ask your question publicly so other students can answer and benefit from your post.
  4. If it turns out that you need to include your code, make a private post and include your code as a code snippet (or submit it to Gradescope so TAs can see it), as opposed to a screenshot (we cannot run screenshots). You can cite a few lines if you believe that makes things clearer. This makes it easier for TAs to understand your code and also allows for smoother debugging.
  5. Please try to avoid using phrases like, “it’s not working, what’s wrong with my code?” Specific details help locate the problem more effectively. To help us narrow down the strategies for diagnosing problems include:
    1. the error or question you have, such as what it is currently doing and what it should be doing
    2. what you have done to test your code
    3. anything you have attempted to do to resolve the issue
  6. Be patient and respectful!

To email or not to email

When considering whether to email the TAs or professor, ask yourself the following:

  1. Could this question be answered by anyone in the class?
  2. Would others in the class benefit from the answer to this question?

If you answer yes to either of the above questions, please post your question on the class forum. This will increase the likelihood of a timely response. A strong reason to email the professor would be something private to you, such as requesting an extension or wanting to discuss special circumstances.

Academic Resource Center

Want expert consultation about study habits, learning, time management, and more? Check out the Academic Resource Center (ARC) at Duke.

Counseling and Psychological Services

Your thriving is about more than this class. If you need to talk to someone, consider Duke Counseling and Psychological Services (CAPS).