Master the fundamentals of automata theory, formal languages, and computational complexity in this advanced computer science course.
Master the fundamentals of automata theory, formal languages, and computational complexity in this advanced computer science course.
This comprehensive course explores the theoretical foundations of computer science through automata theory and formal languages. Students learn about finite automata, regular expressions, context-free grammars, and Turing machines. The course progresses from basic concepts to advanced topics like decidability and computational complexity, including NP-complete problems. Through rigorous mathematical analysis and practical examples, participants develop a deep understanding of theoretical computer science principles and their applications in computational problem-solving.
Instructors:
English
English
What you'll learn
Master the principles of finite automata and regular expressions
Understand context-free grammars and pushdown automata
Explore Turing machines and the concept of decidability
Analyze computational complexity and NP-complete problems
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This advanced computer science course covers the theoretical foundations of computation and language processing. The curriculum progresses from finite automata and regular languages to context-free grammars, Turing machines, and computational complexity theory. Students learn about closure properties, decision algorithms, and pumping lemmas for various language classes. The course culminates in the study of intractability and NP-complete problems, providing a comprehensive understanding of theoretical computer science principles.
Instructor
2 Courses
Pioneering Computer Scientist and Educator
Jeffrey D. Ullman is the Stanford W. Ascherman Professor of Engineering (Emeritus) in the Department of Computer Science at Stanford University and CEO of Gradiance Corp. After earning his B.S. from Columbia University in 1963 and Ph.D. from Princeton in 1966, he worked at Bell Laboratories before joining Princeton's faculty in 1969. In 1979, he moved to Stanford, where he served as chair of the Computer Science Department from 1990 to 1994. Ullman's contributions to computer science span databases, compilers, automata theory, and algorithms, authoring 16 influential books that have shaped generations of computer scientists. His work with Alfred Aho, particularly on compiler design and algorithms, earned them the 2020 Turing Award, the highest honor in computer science. Ullman's numerous accolades include election to the National Academy of Engineering, the American Academy of Arts and Sciences, and prestigious awards such as the Knuth Prize and the IEEE von Neumann medal. At Stanford, he developed courses on database systems, automata theory, and compilers, while also creating innovative online learning platforms through Gradiance Corporation. His teaching and mentorship have profoundly influenced the field, with many of his students becoming distinguished computer scientists in academia and industry.
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