Remember to stay on top of the lecture readings! See syllabus for more info!
Note: unless otherwise noted, all assignments are due at 23:59 (PDT). If you have trouble submitting an assignment and the deadline is approaching, you should email all the files to Hunter BEFORE the deadline so we have your submission on record. Submissions after the late cutoff may not be accepted even if there were technical difficulties turning in the assignment if you did not email us your solution before the cutoff.
Homework 6 - Processing Image Data [40 points]
Homework 6 is due on Thursday, May 28 at 23:59 (PDT) and should be submitted on Ed.
Homework 5 - Processing Geospatial Data [40 points]
Homework 5 is due on Thursday, May 21 at 23:59 (PDT) and should be submitted on Ed.
Homework 4 - Python Classes and Search Engines [40 points]
Homework 4 is due on Thursday, May 7 at 23:59 (PDT) and should be submitted on Ed.
Homework 3 - Data Analysis [40 points]
Homework 3 is due on Thursday, April 30 at 23:59 (PDT) and should be submitted on Ed.
Homework 2 - Processing CSV Data [40 points]
Homework 2 is due on Thursday, April 23 at 23:59 (PDT) and should be submitted on Ed.
Homework 1 - Python Crash Course [40 points]
Homework 1 is due on Thursday, April 16 at 23:59 (PDT) and should be submitted on Ed.
Homework 0 - Infrastructure Setup [5 points]
Homework 0 is due on Thursday, April 9 at 23:59 (PDT) and should be submitted on Ed.
We do not recommend using late days on this assignment by turning it in late. This assignment is worth far fewer points than the other assignments will be.
So far, you have analyzed data from a variety of sources to solve realistic problems from science, engineering, and business. Now it's your turn to choose and analyze a problem. This is good practice for how you will use Python for the remainder of your career. You are highly encouraged to work with a partner or group of two others on this project!
There are four parts to this assignment, due separately.
For some example reports and slides, please refer to our past project gallery.
This project is structured a lot like the project in CSE 160 with some specific requirements changed. You may NOT submit the same project that you used in CSE 160 for this class. You may use the same dataset, but we would expect that you have a much more novel and interesting set of research questions if you use the same dataset as you did in a previous quarter.
We will use Gradescope to submit the various parts of the project since it does a really good job with group projects. We will make Gradescope accounts for everyone and you will receive an email when your account is created. For each part, only one group member should submit on Gradescope. You should use the Group Members functionality to add the appropriate partner(s) if you have them. If you want to learn about how to add Group Members on Gradescope, please see instructions here.
Make sure to see the syllabus for information about partners and late days.
Please make sure you're aware of the following policies:
If you feel you were incorrectly penalized on a homework assignment, use this form to submit a regrade. Regrades will be accepted up to one week after the feedback for that assignment has been released.