Success in this deep learning course requires: strong programming (data structures), linear algebra (matrix operations, vectors), and multivariable calculus (gradients, partial derivatives). Prior coursework in these areas is ideal, but supplemental resources will be provided. Python and Julia programming experience is beneficial. This segment details the necessary background in data structures, linear algebra, and multivariable calculus for success in a deep learning course. It emphasizes the importance of programming experience gained through data structures, highlighting the use of Python and Julia for assignments, and explains how algorithmic efficiency concepts from data structures will be relevant. The speaker clarifies that while a full course in each mathematical subject isn't strictly required, a foundational understanding of key concepts is essential.