Lecture 01
Traditional lecture, live coding / coding demos, and short exercises + solution discussion
Attendance is expected
Opportunity to work on course assignments with TA support
Labs will begin in Week 2 (January 25th) - no lab Week 0 or 1
Posted on Sakai (via Announcements tool)
and sent via email,
Check both regularly.
This course is assessed 100% on your coursework (there is no exam).
We will be assessing you based on the following assignments,
| Assignment | Type | Value | n | Assigned |
|---|---|---|---|---|
| Homeworks | Team | 50% | ~5 | ~ Every other week |
| Midterms | Individual | 40% | 2 | ~ Week 6 and 14 |
| Project | Team | 10% | 1 | ~ Week 10 |
Only work that is clearly assigned as team work should be completed collaboratively (Homeworks + Project).
Individual assignments (Midterms) must be completed individually, you may not directly share or discuss answers / code with anyone other than the myself and the TAs.
On Homeworks you should not directly share answers / code with other teams in this class, however you are welcome to discuss the problems in general and ask for advice.
We are aware that a huge volume of code is available on the web, and many tasks may have solutions posted.
Unless explicitly stated otherwise, this course’s policy is that you may make use of any online resources (e.g. Google, StackOverflow, etc.) but you must explicitly cite where you obtained any code you directly use or use as inspiration in your solution(s).
Any recycled code that is discovered and is not explicitly cited will be treated as plagiarism, regardless of source.
To uphold the Duke Community Standard:
- I will not lie, cheat, or steal in my academic endeavors;
- I will conduct myself honorably in all my endeavors; and
- I will act if the Standard is compromised.
Browser based + Provides consistency in hardware and software environments
Local Python / Jupyter installations are fine but we will not guarantee support
Common issues:
This site can’t be reached make sure you are on a Duke network and are not use an alternative DNS service.If working locally you should make sure that your environment meets the following requirements:
Recent Python (3.10 or newer) with working pip (or equivalent)
Recent jupyterlab (3.5 or newer)
working git installation (jupyterlab-git recommended)
ability to create ssh keys (for GitHub authentication)
All packages should be updated to their latest version (assignments will include requirements.txt when needed)
We will be using an organization specifically to this course
https://github.com/sta663-sp23
All assignments will be distributed and collected via GitHub
All of your work and your membership (enrollment) in the organization is private
We will be distributing a survey this weekend to collection your account names
Some brief advice about selecting your account names (particularly for GitHub),
Incorporate your actual name! People like to know who they’re dealing with. Also makes your username easier for people to guess or remember.
Reuse your username from other contexts, e.g., Twitter or Slack.
Pick a username you will be comfortable revealing to your future boss.
Shorter is better than longer, but be as unique as possible.
Make it timeless. Avoid highlighting your current university, employer,
or place of residence.
Create a GitHub account if you don’t have one
Complete the course survey (you will receive before next Monday)
make sure you can login in to the Department’s RStudio server
Sta 663 - Spring 2023