140.629.81
AI for Public Health in Python
Location
Internet
Term
4th Term
Department
Biostatistics
Credit(s)
4
Academic Year
2025 - 2026
Instruction Method
Online Asynchronous
Auditors Allowed
Yes, with instructor consent
Available to Undergraduate
Yes
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
140.628, prior programming experience, precalculus
mathematics
Enrollment Restriction
This course is not restricted.
Presents the basics of artificial intelligence using the python programming language. Focuses on building knowledge in AI programming using regression models as a foundation. Builds off of regression, then proceeds to artificial neural networks and deep learning. Focuses on practical implementation specifically tied to computational tools. Covers specific neural network architectures, including convolutional neural networks and attention models. Teaches how to download and use public models. Culminates with an AI web app development project chosen by the student.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Implement artificial intelligence programs on novel data sets
- Recognize the connection between artificial neural networks and regression and logistic regression
- Program convolutional neural networks
- Download and use open weight AI models
- Use enterprise AI models with an application program interface
Upon successfully completing this course, students will be able to:
Methods of Assessment
This course is evaluated as follows:
- 33% Homeworks/coding projects
- 33% Quizzes
- 34% Final Capstone Project