Prerequisites: Minimum grade of C- in CMSC320, CMSC330, and CMSC351; and 1 course with a minimum grade of C- from (MATH240, MATH341, MATH461); and permission of the CMNS-Computer Science department.

This course will provide a comprehensive introduction to the fundamental concepts of key modalities and algorithms for multimodal representation learning, alignment, and fusion. Students will learn key concepts, algorithms, and applications centered around multimodal deep learning while gaining hands-on experience with state-of-the-art models and emerging reresearch trends.