AI School 2022
Our first AI school, held virtually, with a focus on both math for AI and key machine-learning methods, taught through applications of Natural Language Processing.
Six evenings, from math to transformers
A summer-school-style mini-course
Math for machine learning (probability and linear algebra) was taught by Raphael Flauger, while machine-learning methods and their applications were taught by Ndapa Nakashole.
Supervised learning depends on labeled data, so the course worked with students to collect high-quality data in Oshikwanyama for applications of interest, using a data annotation tool, letting students take ownership of the ML systems they built. The course was offered free of charge, with certificates on successful completion.