Attendance¶
Attendance and active participation is expeted. You earn level 1 achievements in class and all class sessions are active learning.
If you miss class, you can make it up by reading the posted notes and the prismia transcript. Best practice is to download them as a notebook and run them to make sure you understand each step. If you miss both class sessions in a week, the level one achievements can be made up through annotation or in your assignment.
Absences do not require notification.
Assignment Deadlines and Late Work¶
Late assignments will not be graded. Extensions will not be granted for assignments. Every skill will be assessed through more than one assignment, so missing assignments occasionally will not necessarily impact your grade. If you do not submit any assignments that cover a given skill, you may earn the level 2 achievement in that skill through a portfolio check, but you will have fewer chances to earn level 3 in that skill.
If you submit work that is not complete, it will be assessed and receive feedback. Submitting pseudocode or code with errors and comments about what you have tried could even be enought earn a level 1 achievement. Assignments cover multiple skills, so partially completing the assignment may earn level 2 for one, but not all. Submitting something even if it is not perfect is important to keeping conversation open and getting feedback and help continuously.
Portfolio Deadlines and Extensions¶
Building your Data Science Portfolio should be an ongoing process, where you commit work to your portfolio frequently. If something comes up and you cannot finish all that you would like assessed by the deadline, open an Extension Request issue on your repository at least 24 hours before the deadline.
Fill in the tempalte.
Academic Dishonesty¶
All work must represent your own understanding of both the data science practices and the related programming concepts. Submitting code or prose that was generated by a generative model or another person is not allowed.
If you are found to have submitted work that does not constitute your own work, the following penalties apply:
in a portfolio, all achievements attempted in the dishonest component are permanently ineligible.
in an assignment the level three achievements for the skills of focus in the assignment are ineligible, and the relevent level two for those skills requires meeting the standard for the level 3.
For example, if you are violate the academic honesty policy in asignment 4, Prepare level 3 becomes ineligible and you must meet the requirements for prepare level 3 in a portfolio in order to earn prepare level 2.
If you violate acadmic honesty policy in portfolio 1 while attempting level 3 at Python, access, prepare, summarize and visualize and process level 2, then your maximum grade becomes a B+, because level 3 in all five of those skills becomes inelgible.
Regrading¶
Add comments:
For general questions, post on the conversation tab of your Feedback PR with your request.
For specific questions, reply to a specifc comment.
Re-request a review from Dr. Brown on your Feedback Pull request.
If you think we missed where you did something, add a comment on that line to help us find it
(on the code tab of the PR, click the plus (+) next to the line) and then post
on the conversation tab with an overview of what you’re requesting and tag @brownsarahm