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This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms--supported by motivating examples--that bring meaning to the problems faced by computer programmers. The idea of computational complexity is introduced, demonstrating what can and cannot be computed efficiently at scale, helping programmers make informed judgements about the algorithms they use. The easy-to-read text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python.
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Students of computer science will find this clear and concise textbook invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python.
Dr. Kent D. Lee is a Professor Emeritus of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer books, Python Programming Fundamentals, and Foundations of Programming Languages.
Dr. Steve Hubbard is a Professor Emeritus of Mathematics and Computer Science at Luther College.
Dr. Kent D. Lee is a Professor Emeritus of Computer Science at Luther College, Decorah, Iowa, USA. He now works for Hewlett Packard Enterprise as an Engineer and Architect on the DragonHPC project within the High Performance Computing division (formerly Cray, Inc.). He is the author of the successful introductory companion textbook from Springer, Python Programming Fundamentals, and the Foundations of Programming Languages - an excellent textbook on compiler and interpreter implementation.
Dr. Steve Hubbard is a Professor Emeritus of Mathematics and Computer Science at Luther College.
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