Grading

Warning

Another time, for the people in the back:

  • Unless explicitly noted, all assignments must be completed individually.

  • Changes to submissions after the deadline will be ignored.

  • Missed assignments will receive a zero.

Participation is both on the discussion board and during class. Participation is especially important in this class because it incentivizes staying current; this is not a class where late cramming is viable. Crucially, it will help us build a community where learning this material is less frustrating and more enjoyable.

From most important to (just slightly) less important:

  • In class quizzes (high frequency, low stakes) for knowledge retrieval and attention maintenance

  • “Demos”: In some classes, a few students will present exercises I assignment before class (good faith attempts)

  • Discussion board replies: answering questions and/or moving conversations forward, being helpful and polite

  • Discussion board posts: asking questions-but don’t spam the board with low effort posts, sharing fun and related articles or code snippets (“Look what I found! Maybe this is useful”)1

  • Contributions to in-class discussions

  • In-class coding (mostly effort based)

  • Easter egg hunts on the site and improving our functions (see the “feature requests”)

  • Improving the site/class: finding and fixing typos, suggesting materials

  • If we are doing virtual sessions: Is your camera on when I randomly take snapshots of the gallery?

About 7 assignments. Subject to some fiddling.

  • Each assignment grade will come from an average of two peer reviews (which will be adjusted if they have objective errors or large subjective ones)

  • Peers will review and provide comments, the teaching team will assign grades

  • Unless explicitly noted, all assignments must be completed individually.

  • Changes to submissions after the deadline will be ignored.

  • Missed assignments will receive a zero.

Eight assignments:

  1. Python + GitHub

  2. Pandas

  3. Data visualization

  4. Data wrangling

  5. Regression

  6. Machine Learning

  7. Machine Learning Contest

  8. Personal Website

You should aspire to

  • Write accurate and honest reviews

  • Actually run the code to verify accuracy

  • Give helpful, constructive, and nice feedback

What I love about this is that it puts you on the precipice of truly large-scale analysis. The deliverable for the project is something you can talk about in job interviews. At the end of the project, you’ll have pieces of code that can be used within even larger and interesting projects, and more importantly, an understanding of how to break a seemingly complex task down into manageable pieces.

It’s going to be fun!

See the midterm project description page in the assignments section of the site for more.

Student groups write a proposal outlining a question the group is interested in and their plan to answer it. Over the last month of class, we will work to break your question down into manageable subproblems and solve them one by one to conduct their analysis.

Students develop a website to show their results and present their work to the class.

I’ve really enjoyed this in past years, and look forward to seeing what everyone comes up with!

See the final project description page in the assignments section of the site for more.


1

Obviously, don’t share code used on assignments