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681.3*G2 --- Discrete mathematics (Mathematics of computing) --- Computer science --- Mathematics. --- 681.3*G2 Discrete mathematics (Mathematics of computing) --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Mathematics

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Essential Information about Algorithms and Data Structures A Classic Reference The latest version of Sedgewick, s best-selling series, reflecting an indispensable body of knowledge developed over the past several decades. Broad Coverage Full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing, including fifty algorithms every programmer should know.

Computer algorithms --- Computer science --- algoritmen --- systeemontwikkeling (informatica) --- informatica --- wiskunde --- Algorithmes --- Textbooks. --- Manuels d'enseignement supérieur --- 681.3*G --- 681.3*G Mathematics of computing --- Mathematics of computing --- Algorithms --- Programmeren --- Algoritmen --- Algoritme --- Kind

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Computer science --- Computer arithmetic --- Computer algorithms --- 681.3*G --- Mathematics of computing --- Computer algorithms. --- Computer arithmetic. --- 681.3*G Mathematics of computing --- Digital arithmetic --- Digital computer arithmetic --- Arithmetic --- Computer architecture --- Algorithms

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Parallel programming (Computer science) --- 005.275 --- 681.3*G --- Computer programming --- Parallel processing (Electronic computers) --- 681.3*G Mathematics of computing --- Mathematics of computing --- Programming --- Parallel programming (Computer science).

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This textbook contains the mathematics needed to study computer science in application-oriented computer science courses. The content is based on the author's many years of teaching experience. The translation of the original German 7th edition Mathematik für Informatiker by Peter Hartmann was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content. Textbook Features You will always find applications to computer science in this book. Not only will you learn mathematical methods, you will gain insights into the ways of mathematical thinking to form a foundation for understanding computer science. Proofs are given when they help you learn something, not for the sake of proving. Mathematics is initially a necessary evil for many students. The author explains in each lesson how students can apply what they have learned by giving many real world examples, and by constantly cross-referencing math and computer science. Students will see how math is not only useful, but can be interesting and sometimes fun. The Content Sets, logic, number theory, algebraic structures, cryptography, vector spaces, matrices, linear equations and mappings, eigenvalues, graph theory. Sequences and series, continuous functions, differential and integral calculus, differential equations, numerics. Probability theory and statistics. The Target Audiences Students in all computer science-related coursework, and independent learners. The Author Peter Hartmann is a professor at Landshut University of Applied Sciences in the Department of Computer Science. The focus of his teaching is on mathematics for computer scientists and business informatics specialists.

Computer science --- Mathematics of Computing. --- Mathematical Applications in Computer Science. --- Mathematics. --- Computer mathematics --- Electronic data processing --- Mathematics