Foundational Mathematics of Artificial Intelligence
Summer 2026
AS.110.110, a JHU pre-college summer course: data, regression, classification and neural networks in Python.
A course for high school students on the mathematics behind machine learning. Each day combines a lecture, a guided Python walkthrough in a Jupyter notebook, a hands-on activity and short reflection questions. The course ends with a group project on a real dataset.
Class notes
(OneNote, written in class)
Daily outline
Day 1: Introduction
- Neural Network Playground
- Introduction to Python
Day 2: Modeling and descriptive statistics
- Cleaning real datasets (penguins, car fuel economy)
- Overfitting example
Day 3: Regression
- Predicting penguin body mass and fuel economy
- Activity: plot and minimize the \(L^1\) error of a line through data
Day 4: Supervised learning and classification
- Classifying penguin species and car origin
- Google’s Teachable Machine
- ML Playground
- Activity: an animal guessing game
Day 5: Multiple linear regression and dimension reduction
Day 6: Neural networks
- Neural Network Playground
- Activity: a mystery network worksheet
Day 7: Convolutional neural networks
- CNN visualization
- Activity: mystery filters and a worked example of a convolution
Day 8: Using pre-trained models
- Using a pre-trained model from Hugging Face