Designed for CS0 and CS1 courses, this textbook teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. It uses Python as the lab software so that students can seamlessly transition from introductory projects to more advanced studies in later courses. The interactive lab projects in each chapter allow students to examine important ideas in computer science. The Python software modules for each lab project are available online.
Designed for CS0 and CS1 courses, this textbook teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. It uses Python as the lab software so that students can seamlessly transition from introductory projects to more advanced studies in later courses. The interactive lab projects in each chapter allow students to examine important ideas in computer science. The Python software modules for each lab project are available online.
John S. Conery is a professor in the Department of Biology and the Institute of Ecology and Evolution at the University of Oregon, where he teaches computer science courses and is developing introductory programming courses for biology majors. As a professor of computer and information science, he taught introductory computer science courses as well as courses on high performance computing and computational science. His research in bioinformatics and computational biology spans a number of areas related to gene and genome duplication, artificial neural networks, population modeling, and systems biology. He received a Ph.D. in computer science.
Inhaltsangabe
Introduction. The Python Workbench. The Sieve of Eratosthenes. A Journey of a Thousand Miles. Iteration as a Strategy for Solving Computational Problems. Breaking Large Problems into Smaller Subproblems. A Machine Learning Approach to Filtering Junk Mail. An Algorithm for Generating Random Numbers. Binary Codes and Algorithms for text Compression and Error Detection. Introduction to Computer Architecture and Assembly Language Programming. A Program that Understands English (or does it). Computer Simulation and the N-Body Problem. A Genetic Algorithm for a Computationally Demanding Problem.
Introduction. The Python Workbench. The Sieve of Eratosthenes. A Journey of a Thousand Miles. Iteration as a Strategy for Solving Computational Problems. Breaking Large Problems into Smaller Subproblems. A Machine Learning Approach to Filtering Junk Mail. An Algorithm for Generating Random Numbers. Binary Codes and Algorithms for text Compression and Error Detection. Introduction to Computer Architecture and Assembly Language Programming. A Program that Understands English (or does it). Computer Simulation and the N-Body Problem. A Genetic Algorithm for a Computationally Demanding Problem.
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