Discovering Computer Science - Havill, Jessen
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Présentation Discovering Computer Science Format Relié
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Résumé : Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines.
Biographie: Jessen Havill is a Professor of Computer Science at Denison University. He has been teaching courses across the computer science curriculum for almost thirty years, and was awarded the College's highest teaching honor, the Charles A. Brickman Teaching Excellence Award, in 2013. Although his primary expertise is in the development and analysis of online algorithms, Dr. Havill has spent many years collaborating with colleagues across the curriculum to develop interdisciplinary academic opportunities for students. From 2016-2019, he became the founding Director of Denison University's interdisciplinary Data Analytics program. Dr. Havill earned his bachelor's degree from Bucknell University and his Ph.D. in computer science from The College of William and Mary.
Sommaire: Preface Acknowledgments About the author How to Solve It UNDERSTAND THE PROBLEM DESIGN AN ALGORITHM WRITE A PROGRAM LOOK BACK SUMMARY AND FURTHER DISCOVERY Visualizing Abstraction DATA ABSTRACTION DRAWING FLOWERS AND PLOTTING EARTHQUAKES FUNCTIONAL ABSTRACTION PROGRAMMING IN STYLE A RETURN TO FUNCTIONS SCOPE AND NAMESPACES SUMMARY AND FURTHER DISCOVERY Inside a Computer COMPUTERS ARE DUMB EVERYTHING IS BITS COMPUTER ARITHMETIC BINARY ARITHMETIC THE UNIVERSAL MACHINE Growth and Decay ACCUMULATORS DATA VISUALIZATION CONDITIONAL ITERATION CONTINUOUS MODELS NUMERICAL ANALYSIS SUMMING UP FURTHER DISCOVERY PROJECTS Forks in the Road PSEUDORANDOM NUMBER GENERATORS SIMULATING PROBABILITY DISTRIBUTIONS BACK TO BOOLEANS DEFENSIVE PROGRAMMING GUESS MY NUMBER SUMMARY AND FURTHER DISCOVERY PROJECTS Text, Documents, and DNA FIRST STEPS TEXT DOCUMENTS A CONCORDANCE WORD FREQUENCY TRENDS COMPARING TEXTS TIME COMPLEXITY COMPUTATIONAL GENOMICS SUMMARY AND FURTHER DISCOVERY PROJECTS Data Analysis SUMMARY STATISTICS WRANGLING DATA TALLYING FREQUENCIES READING TABULAR DATA DESIGNING EFFICIENT ALGORITHMS LINEAR REGRESSION DATA CLUSTERING SUMMARY AND FURTHER DISCOVERY PROJECTS Flatland TABULAR DATA THE GAME OF LIFE DIGITAL IMAGES SUMMARY AND FURTHER DISCOVERY PROJECTS Self-similarity and Recursion FRACTALS RECURSION AND ITERATION THE MYTHICAL TOWER OF HANOI RECURSIVE LINEAR SEARCH DIVIDE AND CONQUER LINDENMAYER SYSTEMS 9SUMMARY AND FURTHER DISCOVERY PROJECTS Organizing Data BINARY SEARCH SELECTION SORT INSERTION SORT EFFICIENT SORTING TRACTABLE AND INTRACTABLE ALGORITHMS SUMMARY AND FURTHER DISCOVERY PROJECTS Networks MODELING WITH GRAPHS SHORTEST PATHS IT'S A SMALL WORLD RANDOM GRAPHS SUMMARY AND FURTHER DISCOVERY PROJECTS Object-oriented Design OPERATORS AND POLYMORPHISM A FLOCKING SIMULATION A STACK ADT A DICTIONARY ADT SUMMARY AND FURTHER DISCOVERY PROJECTS Bibliography Appendix A ? Python Library Appendix B ? Selected Exercise
RANDOM WALKS
SIMULATING AN EPIDEMIC
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