First-order logic is a collection of formal systems used in mathematics, philosophy, linguistics and computer science which uses quantified variables over non-logical objects. It is distinguished from propositional logic by its use of quantifiers and relations, and can be used to create theories about topics such as set theory and arithmetic. It has been studied extensively in proof theory and automated theorem proving.
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.
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+ 23 more conceptsStanford University
Autumn 2022-2023
Stanford's CS 221 course teaches foundational principles and practical implementation of AI systems. It covers machine learning, game playing, constraint satisfaction, graphical models, and logic. A rigorous course requiring solid foundational skills in programming, math, and probability.
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+ 88 more conceptsStanford University
Fall 2019
This course emphasizes SAT and SMT technology and its applications, offering an understanding of theoretical foundations and how to implement a small theory solver. Applications of SAT/SMT technology in the context of verification are also covered. The advanced topics and lack of specified prerequisites suggest this is a high-level course.
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+ 20 more conceptsBrown 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.
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+ 26 more conceptsCarnegie Mellon University
Spring 2019
This course from Carnegie Mellon University provides a deep understanding of AI's theory and practice, covering methods for decision-making, problem-solving, and handling uncertainty. Topics include search algorithms, computational game theory, and AI ethics.
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+ 24 more conceptsStanford 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.
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+ 10 more concepts