Semester Schedule#
Schedule is subject to change, but if changes are made, students will be notified.
Assignment Due Dates#
Pre-Class Assignments: Always due by 11:59pm the night before each class session unless otherwise stated.
In-Class Assignments: Always due by 12:00pm (noon) immediately after each class session.
Below are a list of due dates for other assigmments, including Homework, the Code Portfolio, and the Semester Project.
Date |
Assignment |
|---|---|
May 22 |
Homework #1 due by 11:59pm |
May 30 |
Homework #2 due by 11:59pm |
June 6 |
Homework #3 due by 11:59pm |
June 6 |
Project Plan due by 11:59pm |
June 15 |
Homework #4 due by 11:59pm |
June 24 |
Final Project Notebook due by 11:59pm |
June 26 |
Homework #5 due by 11:59pm |
June 26 |
Peer Assessment due by 11:59pm |
Class Schedule#
Below is information about what we’ll be doing on each day of class. Class attendance is mandatory unless otherwise stated. If you are sick or otherwise unable to attend, please email jdelker@msu.edu before class to let me know.
Date |
Day |
Topic(s) |
|---|---|---|
May 11 |
01 |
Class expectations, pre-course survey, sorting algorithm activity |
May 12 |
02 |
Introduction to Python, variables, order of magnitude estimates |
May 13 |
03 |
Lists and loops |
May 14 |
04 |
Data ethics, academic integrity, and good coding practices |
May 18 |
05 |
Conditional arguments, if statements, and introduction to functions |
May 19 |
06 |
Functions |
May 20 |
07 |
Generative AI Use, Review of Concepts |
May 21 |
08 |
Quiz 1; Python modules (e.g. math and matplotlib) |
May 25 |
– |
NO CLASS |
May 26 |
09 |
NumPy basics (loading and plotting data), the correlation coefficient |
May 27 |
10 |
Basic statistics and introduction to Pandas |
May 28 |
11 |
Pandas |
June 1 |
12 |
Working with unprocessed data |
June 2 |
13 |
Finding resources online and tinkering with code |
June 3 |
14 |
Linear regression #1 (evaluating model fits) |
June 4 |
15 |
Quiz 2; Linear regression #2 (fitting curves to data) |
June 8 |
16 |
Solving ordinary differential equations numerically |
June 9 |
17 |
Solving ordinary differential equations with |
June 10 |
18 |
Compartmental Modeling #1 |
June 11 |
– |
NO CLASS |
June 15 |
19 |
Compartmental Modeling #2 |
June 16 |
20 |
Using plots effectively (data visualization) |
June 17 |
21 |
2D NumPy Arrays and Image Analysis |
June 18 |
22 |
Quiz 3; Agent-based modeling #1 |
June 22 |
23 |
Agent-based modeling #2 |
June 23 |
24 |
Data Ethics and Algorithmic Bias |
June 24 |
25 |
Structured Project Work Day |
June 25 |
26 |
Quiz #4 and Project Presentations |