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Discrete Mathematics
with applications in Computer Science
This textbook accompanies a year-long Discrete Mathematics course for Computer Science and AI students, covering classical topics such as combinatorics, graph theory, probability, logic, and set theory. It emphasizes applications across computer science and complements the standard curriculum with advanced topics in each chapter.
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About the Book
This textbook accompanies our year-long course on Discrete Mathematics in the Computer Science and Artificial Intelligence B.S. program at Neapolis University Pafos. It covers all the classical topics: combinatorics, graph theory, probability theory, logic, and set theory. It also presents many applications of these topics in different areas of computer science: artificial intelligence, bioinformatics, coding theory, complexity theory, cryptography, data structures and algorithms, programming language theory, and formal methods. Together, we will see many ways to use these ideas in practice. Each chapter also includes advanced topics that are not covered in standard discrete mathematics courses.
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About the Authors
Alexander S. Kulikov
Alexander S. Kulikov is a researcher at JetBrains where he is also the Head of the Algorithms and Complexity Lab. At Neapolis University Pafos, he is the Head of the Computer Science and Artificial Intelligence BS program. His research interests include algorithms and complexity theory. He co-authored online courses "Data Structures and Algorithms" and "Introduction to Discrete Mathematics for Computer Science" that are available at Coursera and edX.
Nikolai Chukhin
Nikolai Chukhin is a Research Assistant at the Algorithms and Complexity Theory Lab at JetBrains Research. His research interests include computational complexity and fine-grained complexity. He graduated with honors from Saint Petersburg University and Neapolis University Pafos and has taught graph theory at Neapolis University Pafos.
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