# CMU 11-785: Introduction to Deep Learning ## Descriptions - Offered by: CMU - Prerequisites: Linear Algebra, Probability, Python Programming, and ML Foundations - Programming Languages: Python - Difficulty: 🌟🌟🌟🌟🌟 - Class Hour: ~120 hours CMU 11-785 is a rigorous, fast-paced deep learning core course with very little filler. It starts from neural network fundamentals and systematically covers CNNs, RNNs, Attention/Transformers, optimization, and generalization. The workload feels close to graduate-level training: assignments usually require real understanding of model behavior, training details, and experimental methodology. If you want durable deep learning fundamentals (instead of only using high-level APIs), this course is an excellent investment. ## Course Resources - Course Website: - Recordings: Lecture recordings are available on course websites (varies by semester) - Textbooks: Mainly Lecture Notes / Slides + paper readings - Assignments: Multiple programming assignments and a course project (published on course sites) ## Personal Resources No public personal repository is currently provided for this course.