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MATH:5760:0AAA Mathematical Biology II
Spring 2026
Time: 12:30P - 1:45P TTh    Location: S118 LC

Instructor:  Dr. Isabel K. Darcy
Department of Mathematics and AMCS
University of Iowa
Office: MLH 25J
Phone: 319-335- 0770
Email: isabel-darcy AT uiowa.edu

Ways to get help:

Your grade will be based on

Grading will be based on a point system, so if you have earned enough points for your desired grade, you do not need to take the final exam. Your main focus in this class is to create a project/portfolio so that it is an excellent resource for you to review techniques in future years.

TENTATIVE CLASS SCHEDULE-ALL DATES SUBJECT TO CHANGE (click on date/section for file of corresponding class material):

Tentative ScheduleHW/Announcements -- replace with references
Week 1
1/20 Introduction to data analysis HW: Create github account
1/22 LAB 1: Introduction to Github 1,
Introduction to Python,
Week 2
1/27 Intro to ML HW:
1/29 LAB 1: Introduction to Github 2;
Python: data wrangling
Week 3
2/3 PCA HW: due Friday 2/6
Lab 1
2/5 LAB 2: linear regression
Week 4
2/10 Linear Regression HW: due Friday 2/13
Lab 2,   Create personal webpage on Github
2/12 Lab 4: Introduction to Git, Intro to PCA, Linear regression
Week 5
2/17 MultipleLinear Regression HW: due Friday 2/20
Lab 3,    Project draft 1,    poster idea
2/19 Lab 5:
Week 6
2/24 Clustering HW: due Friday 2/27
Lab 4,    poster draft
2/26 Lab 6:
Week 7
3/3 Presentations: Illustrate something you have learned.
AI 		HW: due Friday 3/6
Lab 5,    Project draft 2   
3/5 Presentations: Illustrate something you have learned.
Week 8
3/10 Midterm Exam
3/12 Github
***** Spring Break March 15 - 22 ****
Week 9
3/24 Logistic Regression
3/25 Shrinkage
Week 10
3/31 Logistic Regression Voronoi (6:06 min) and k-means (9:10 min)
4/2 Test/Train, Data Leakage, Bias/Variance, Shrinkage
Week 11
4/7
4/9
Week 12
4/14 Presentations: Use artificial or real data to illustrate something.
neural networks and deep learning
4/16 neural networks and deep learning
Week 13
4/21 neural networks and deep learning
4/23 neural networks and deep learning
Week 14
4/28 Ethics, reproducible research, publication bias, data privacy
4/30 Lab wrap-up
Week 15
5/5 Presentations

5/7 Presentations, Review
Final's week
TBA Final exam: TBA

References:

An Introduction to Statistical Learning with applications in Python, http://www.statlearning.com
Scikit-learn Machine Learning in Python, available at https://scikit-learn.org
StatQuest: eg: https://statquest.org/video-index/, https://statquest.org/neural-networks-part-1-inside-the-black-box/