Throughout the semester we will have a number of group discussions that ask you to respond to a reading or video as well as your fellow classmates.

Discussion 1 - Introductions and Interests

Welcome! This course brings together students from around the world with unique work, life, and educational experiences. You will get to engage and develop working relationships with many of these fellow students. This is your chance to learn a bit more about your peers.

Update Your Canvas Profile Make sure that your Canvas profile is up to date. To do this, select “Account”, then “Profile” on the menu bar. Here you can add an image, your contact details, bio, and links to other platforms such as LinkedIn.

Introduce Yourself! Record a short introductory video of 1–2 minutes. Use the following questions as a guideline for sharing more about yourself so that we can get to know you better:

  1. Where do you currently reside (state or country)?
  2. What is your professional background?
  3. What is a hobby that you enjoy doing?
  4. What would you like to learn or achieve from this course?

Upload Your Video and Respond!

  • Ideally, upload your video as an MP4 file.
  • To upload, click “Reply” below and then “Insert” on the toolbar.
  • On the dropdown menu, select “Media” then “Upload/Record Media”.
  • Once the file is uploaded, click the “Post” button.
  • To comment on someone else’s video, click “Reply” and use a hashtag and their name.

Discussion 2 - Concrete Datasets and Proposals

As a means of kicking off a conversation and potentially teaming up for the tutorial, please write a few sentences for the following prompts.

  1. List two datasets (with links) that you are interested in exploring for the final tutorial.
  2. For each of these two datasets, give two concrete questions that you would be interested in exploring.

Discussion 3 - Data Science Ethics Concerns

One of the biggest aspects of applied data science is questions around data privacy and the societal implications there of. Let’s engage in a discussion around these issues by looking at the following articles.

  1. Engaging the Ethics of Data Science In Practice, Communications of the ACM, 2017.
  2. Palantir Has Secretly Been Using New Orleans to Test It’s Predictive Policing Technology, The Verge, 2018.
  3. Welcome to the Age of Privacy Nihilism, The Atlantic, 2018.
  4. What Does GDPR Mean for Me? An Explainer. The Conversation, 2018.

These are four somewhat different articles. The first deals with some issues in DS education and things to think about as you go forth and work with data. The second is an example (and a local one) of some of the unchecked issues surrounding data. The last two deal with privacy in the modern age, the implications of joining data together (what we just learned to do!) and some new regulations in the EU about data privacy.

There are many many more articles out there that deal with data and its applications to a host of problems. Feel free to post about a different article that comes from a major media outlet or reputable journal (with citation).

  1. For ONE of the articles (or one you find), write a post about what you felt was the main take away, and how it relates to an issue in your planned professional life or even your personal/student life now. What are the data or ethical issues at play? Is there anything that you can identify to change?

  2. Followup with TWO other people’s posts – is there something that was overlooked from the articles, is there another resource or perspective to their post you can bring? You should try to comment on someone writing about an article other than the one you did.

Discussion 4 - Project Pitch Peer Feedback

As a means of providing more feedback to other students and helping them develop their projects please do the following. Note that comments should be substantive and be something to which one can reply. Just posting interesting presentation or similar will receive no points. Ask a question about the model, suggest an additional analysis, or critique an assumption!

  1. Comment or post a question on two presentation.
  2. Followup on two different post for a different project and provide additional feedback or thoughts.

Discussion 5 - Final Tutorial Presentation Peer Feedback

As a means of providing more feedback to other students and helping them develop their projects please do the following. Note that comments should be substantive and be something to which one can reply. Just posting interesting presentation or similar will receive no points. Ask a question about the model, suggest an additional analysis, or critique an assumption!

  1. Comment or post a question on two presentation.
  2. Followup on two different post for a different project and provide additional feedback or thoughts.

Discussion Grading Rubric (5 Points Each)

  • (5 Points) Discussion Responses: In all discussions you are required to make a main post which responds to the prompt in a thoughtful way. These should, in general be shorter (about one paragraph, 80-150 words) and please do not drone on like ChatGPT, I will take points away for long and rambling posts. You have also posted at least 2 replies to your fellow students that are respectful and provide a point of discussion (i.e., not “nice job” or “ok”).
Full Good Okay Lacking No Marks
You completely and fully met the criteria described. You have met most of the criteria but lack sufficient depth and/or missed one or more minor pieces. You have missed components of the required criteria and/or they are incorrect / inappropriate or lack depth. You have missed major components of the required criteria and/or may of them are incorrect. Missing or completely inadequate.