AI Math with Public Health Applications Workshop
This workshop is designed for learners 18 years old or older who are entering post-secondary in September 2024 and undergraduate students from a non-STEM discipline eager to explore the intersection of mathematics and artificial intelligence in the context of public health. Participants will delve into the fundamentals of machine learning, focusing on supervised learning techniques.
The workshop centres around a practical application: an infectious disease outbreak prediction model, highlighting its critical role in enhancing public health preparedness. No prior experience in AI or programming is required; the curriculum is tailored for learners encountering this material for the first time. By the end of the workshop, attendees will have gained proficiency in essential mathematical concepts such descriptive statistics for exploratory data analysis, machine learning model as an approximation of a mathematical function, vectors as representations of objects and matrices as stacks of vectors that model a dataset, model training as fitting functions to data, regression to make the prediction, derivatives to maximize predictive performance, root mean square error (RMSE) for model evaluation, uncertainty as a measure of prediction confidence, and related concepts.
The workshop is developed as a supportive and inclusive environment aimed at nurturing diverse talent in AI and mathematics. Spaces are limited, so register now to secure your place and embark on a journey into the dynamic fields of AI and public health.
The workshop runs Monday, August 12 to Friday, August 16 from 10 a.m. – 4 p.m. ET.
For inquiries, please contact Jean-Jacques Rousseau at jrousseau@schulich.yorku.ca.
