Mabdel-03/MIT_GTL_Morocco_IEG

Repo containing all code and data needed for machine learning exercises for IEG students during IAP 2025 MIT Global Teaching Labs Morocco. Code/data generated by Mahmoud Abdelmoneum (mabdel03@mit.edu), and taught by Mahmoud Abdelmoneum and Nicolas Stone Perez (nstonep@mit.edu). # MIT GTL Morocco IAP 2025 IEG Machine Learning Material Repo containing all code and data needed for machine learning exercises, alongside associated lectures for IEG Lycée Français Guy de Maupassant and Lycée Français Sophie Germain students (K-12 grades 9 and 10) during IAP 2025 MIT Global Teaching Labs Morocco. Code/data generated by Mahmoud Abdelmoneum (mabdel03@mit.edu), and taught by Mahmoud Abdelmoneum and Nicolas Stone Perez (nstonep@mit.edu). # Note From Mahmoud and Nicolas We taught this course from January 6th 2025 through January 24th 2025. For the school weeks of January 6th and January 13th we taught at Lycée Français Guy de Maupassant in Casablanca, Morocco. For the week of January 20th we taught at Lycée Français Sophie Germain in Rabat, Morocco. Each week there was a different set of kids who were at different levels with respect to math and programming experience. For the week of 1/6, the students were all in their last year of middle school, and had no python programming experience (only Scratch), and little to no algebra experience. For the week of 1/13, the students had both basic python and basic algebra experience. For the week of 1/20, the students were about a 50/50 split of python/algebra and no python/no algebra experience. Subsequently, each week had slightly different material. The content for the course that we published is that which we taught to the students of Lycée Français Sophie Germain on the week of 1/20. It is geared towards a mixed audience. The theoretical content is challenging for both groups of students, giving them an understanding of the real theoretical foundation of machine learning, while abstracting away a lot of the math such that they do not need to know linear algebra and calculus to learn the material. # Prerequisites As we mentioned in our previous note, this course abstracts away most of the rigorous math that underlies machine learning. To truly understand the theory underlying machine learning, we encourag …