The math foundations of Computer Science are the fundamental skills to understand advanced fields in Computer Science, and also the key to more advanced topics such as Theoretical Computer Science. It includes a range of topics such as Discrete Mathematics, Probability Theory, Combinatorics etc.
Courses of Math Foundations usually requires high school algebra knowledge.
Brown University
Spring 2022
This analytical course dives into the mathematical underpinnings of computing successes like machine learning and cryptography, emphasizing the role of probability, randomness, and statistics. Students will explore mathematical models, theorems, and proofs. Practical implementations are not covered, focusing instead on the theories driving computational probabilities.
Brown University
Spring 2023
CSCI 0220 provides a foundation in discrete math and probability theory. Key topics include logic, set theory, number theory, combinatorics, graph theory, and probability. No prior math background assumed. Aims to develop problem solving, communication, and collaboration skills. Introduces new concepts and ways of thinking to enable analyzing problems arising in computer science. Beginner-friendly introduction to core mathematical concepts underlying many aspects of CS.
Stanford University
Winter 2023
CS 103 introduces mathematical logic, proofs, and discrete structures, paving the way to an understanding of computational problem-solving. It encourages a profound appreciation of mathematical beauty while addressing concepts like finite automata and regular expressions. CS106B is a prerequisite or corequisite. The course also incorporates programming assignments.
Stanford University
Spring 2023
This course offers a thorough understanding of probability theory and its applications in data analysis and machine learning. Prerequisites include CS103, CS106B, and Math 51 or equivalent courses.
Carnegie Mellon University
Spring 2021
This advanced course reexamines traditional concepts of discrete mathematics (relations, functions, logic, graphs, algebra, automata) in the context of computation and algorithms, necessitating a strong background in discrete math.