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Course Materials

Important Course information

Day 01

Day 1 In-Class Assignment: Introductions and Sorting Algorithms

Day 02

Day 2 Pre-class Assignment: Intro to Python
Day 2 In-class Assignment: Order of Magnitude Modeling

Day 03

Day 3: Pre-Class Assignment: Lists and Loops
Day 3 In-class Assignment: The power of compound interest

Day 04

Day 4 Pre-class Assignment: Introduction to Data Ethics: Data and Algorithmic Bias
Day 4 In-class Assignment: Data and Algorithmic Bias, Academic Integrity, and Coding Best Practices

Day 05

Day 5 Pre-class Assignment: Boolean logic, if statements, and an introduction to functions
Day 5 In-class Assignment: Savings for Everyone

Day 06

Day 6 Pre-class Assignment: Thinking more about functions
Day 6 In Class Assignment: A Scurry of Squirrels in Central Park

Day 07

Day 7 Pre-Class Assignment: A reflection on what you’ve learned so far!
Day 7 In-class Assignment: Reviewing and practicing prior concepts
Day 7 In-class Assignment: Reviewing and practicing prior concepts (Solutions)
Practice with Debugging

Day 08

Day 8 Pre-Class Assignment: Python Modules: Numpy and Plots
Day 8 In-class Assignment: Visualizing population growth

Day 09

Day 9 Pre-Class: Introduction to NumPy
michigan_pop.csv
Day 9 In-class Assignment: Exploring Great Lakes Water Levels using NumPy
lake_erie.csv
lake_michigan_huron.csv
lake_ontario.csv
lake_superior.csv

Day 10

Day 10 Pre-class Assignment: Computational Models Overview and The Pandas Data Analysis Library
heart_disease_data.csv
Day 10 In-Class: Cleaning and Analyzing Economic Data
API_NY.GDP.MKTP.CD_DS2_en_csv_v2_31795.csv

Day 11

Day 11 Pre-class Assignment: Normal Distributions, Masking, and Log Plots
GDP_Cleaned.csv
Day 11 In-class Assignment: Get the Lead Out: Understanding The Water Crisis in Flint, MI
flint_water_data.csv

Day 12

Day 12 Pre-Class Assignment: Overview of data and file formats
us_pop_by_state_2010_2011.csv
us_pop_by_state_2012_2013_encoding_utf-16be.csv
us_pop_by_state_2014_2015_windows_linefeed.csv
us_pop_by_state_2016a.csv
us_pop_by_state2017a.yaff
us_pop_by_state_2018_2019.bin
Day 12 In-Class: Overview of data and file formats; US Population and Representation

Day 13

Day 13 Pre-class Assignment: Finding resources online and tinkering wth code
Day 13 In-Class: Using online resources (code and data)

Day 14

Day 14 Pre-Class Assignment: Making Predictions Using Data
Day 14 In-Class Assignment: Evaluating Models

Day 15

Day 15 Pre-Class Assignment: Fitting functions to data (curve-fitting) and thinking more about models
Day 15 In-Class Assignment: (Thoughtfully) fitting models to data
pop200.csv
pop300.csv

Day 16

Day 16 Pre-class Assignment: Introduction to Modeling with Ordinary Differential Equations
Day 16: In-class Assignment: Introduction to Modeling with ODEs

Day 17

Day 17: Pre-class Assignment: Modeling with Ordinary Differential Equations
Day 17: In-class Assignment: Modeling with ODEs

Day 18

Day 18 Pre-Class: Viral Kinetics
Day 18 In-class Assignment: Building Compartmental Models

Day 19

Day 19 Pre-class Assignment: ZOMBIES!!
Day 19 In-Class Assignment: Compartmental Modeling, moving from the model to the code

Day 20

Day 20 Pre-class Assignment: Introduction to Data Visualization
Day 20 In-Class: Introduction to Data Visualization

Day 21

Day 21 Pre-Class: 2D NumPy Arrays
cars.csv
example.jpeg
Day 21 In-Class Assignment: Image Analysis
beach.jpeg
landscape.jpeg
zebra.png

Day 22

Day 22 Pre-class: Agent-based models and forest fires
Day 22 Part 1 In-class Assignment: Modeling forest fires with an Agent-based Model

Day 23

Day 23 Pre-class: More practice manipulating 2D Numpy Arrays
Day 23 In-class Assignment: Modeling forest fires with an Agent-based Model (Part II)

Day 24

Day 24 Pre-Class - Data Dilemmas: Ethics in an Algorithmic World
Data Generation Sheet
Day 24 - In-Class - Data Dilemmas: Ethics in an Algorithmic World

Day 25

Day 25 Pre-class: Project Draft Presentation Preparation
Day 25 In-class Assignment: Project Work Day

Homework

Homework 1 - Python Fundamentals
Homework 2: Dictionaries, If Statements, Functions, and Modules
labor_data.csv
Homework 3: Loading, Cleaning, Analyzing, and Visualizing Data with Pandas (and using resources!)
who_ambient_air_quality.csv
ukulele_data.csv
Homework 4 - Compartmental Models + Data Visualization
auto.csv
Homework 5: 2D Arrays, Agent-based Modeling, and Data Ethics (EXTRA CREDIT)
Spartan.jpg

Code Portfolio

Code Portfolio Assignment
Code Portfolio Example

Semester Project

Semester Project Details
Project Checkpoint
CMSE 201 Final Project Template
Zip file of example projects
Requirements and Grading Rubric
Peer Assessment Notebook
Presentation Evaluation Rubric

Practice Notebooks

Practice with: if statements
Practice with: functions
Practice with: matplotlib
Practice with: Pandas
weather.csv
Practice with: SciPy curve_fit
Practice with: Compartmental Models
Practice with: solve_ivp

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By the Department of Computational Mathematics, Science and Engineering at Michigan State University

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