Scientific And Engineering Problem Solving With The Computer

An introductory computer applications course for students in both the humanities and physical sciences.

This title is designed for undergraduate courses in computing or computer applications taken by engineering or science students. A brief introduction to basic computer concepts is followed by discussion of the various categories of software available for meeting the different types of tasks facing the engineer or scientist. The book includes coverage of spreadsheets, equation solving, database management, word processing, communication, graphics and utility.

"Whether you're a novice or a seasoned professional, there's an Aha! moment in this book for everyone." - James Watson, Adaptive ”Highly recommended to everyone interested in deepening their understanding of Python and practical computer science.” —Daniel Kenney-Jung, MD, University of Minnesota Key Features • Master formal techniques taught in college computer science classes • Connect computer science theory to real-world applications, data, and performance • Prepare for programmer interviews • Recognize the core ideas behind most “new” challenges • Covers Python 3.7 Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About The Book Programming problems that seem new or unique are usually rooted in well-known engineering principles. Classic Computer Science Problems in Python guides you through time-tested scenarios, exercises, and algorithms that will prepare you for the “new” problems you’ll face when you start your next project. In this amazing book, you'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. As you work through examples for web development, machine learning, and more, you'll remember important things you've forgotten and discover classic solutions that will save you hours of time. What You Will Learn • Search algorithms • Common techniques for graphs • Neural networks • Genetic algorithms • Adversarial search • Uses type hints throughout This Book Is Written For For intermediate Python programmers. About The Author David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. He is the author of Dart for Absolute Beginners (Apress, 2014), Classic Computer Science Problems in Swift (Manning, 2018), and Classic Computer Science Problems in Java (Manning, 2020) Table of Contents 1. Small problems 2. Search problems 3. Constraint-satisfaction problems 4. Graph problems 5. Genetic algorithms 6. K-means clustering 7. Fairly simple neural networks 8. Adversarial search 9. Miscellaneous problems

The author shows how using computers and FORTRAN 95 it is possible to tackle and solve a wide range of problems as they might be encountered in engineering or in the physical sciences.

"Introduction to Computational Science" was developed over a period of two years at the University of Utah Department of Computer Science in conjunction with the U.S. Department of Energy-funded Undergraduate Computation in Engineering Science (UCES) program. Each chapter begins by introducing a problem and then guiding the student through its solution. The computational techniques needed to solve the problem are developed as necassary, making the motivation for learning the computing alwasy apparent. Each chapter will introduce a single problem that will be used to motivate a single computing concept. The notes currently consist of 15 chapters. The first seven chapters deal with Maple and the last eight with C. The textbook will contain 20 to 30 chapters covering a similar mix of concepts at a finer level of detail.

Developed over a period of two years at the University of Utah Department of Computer Science, this course has been designed to encourage the integration of computation into the science and engineering curricula. Intended as an introductory course in computing expressly for science and engineering students, the course was created to satisfy the standard programming requirement, while preparing students to immediately exploit the broad power of modern computing in their science and engineering courses.

Unique in its approach, this introduction to computation shows how to think algorithmically and focuses on problem solving with the C programming language.KEY TOPICS:It considers many different algorithmic areas, including numerical methods, matrix methods, sorting, searching, graphics and simulation, and introduces object-oriented programming methods, including C++.For computer programmers and software engineers.

Developed over a period of two years at the University of Utah Department of Computer Science, this course has been designed to encourage the integration of computation into the science and engineering curricula. Intended as an introductory course in computing expressly for science and engineering students, the course was created to satisfy the standard programming requirement, while preparing students to immediately exploit the broad power of modern computing in their science and engineering courses.