Under One Condition An Introduction To Computer Science Principles And Programming In Python

Under One Condition: An Introduction to Computer Science Principles and Programming in Python is designed for curious middle school and building high school students. This book covers topics including design and development, computing errors, abstraction, mutability, computer networks, safe computing, and the many aspects of data.

This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic.

Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms. Summary Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms. You’ll work through a series of exercises based in computer science fundamentals that are designed to improve your software development abilities, improve your understanding of artificial intelligence, and even prepare you to ace an interview. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Whatever software development problem you’re facing, odds are someone has already uncovered a solution. This book collects the most useful solutions devised, guiding you through a variety of challenges and tried-and-true problem-solving techniques. The principles and algorithms presented here are guaranteed to save you countless hours in project after project. About the book Classic Computer Science Problems in Java is a master class in computer programming designed around 55 exercises that have been used in computer science classrooms for years. You’ll work through hands-on examples as you explore core algorithms, constraint problems, AI applications, and much more. What's inside Recursion, memoization, and bit manipulation Search, graph, and genetic algorithms Constraint-satisfaction problems K-means clustering, neural networks, and adversarial search About the reader For intermediate Java programmers. About the author David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. 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 10 Interview with Brian Goetz

Shows how programs can be used to build multimedia computer science applications that include sound, graphics, music, pictures, and movies. The students learn a key set of computer science tools and topics, as well as programming skills; such as how to design and use algorithms, and practical software engineering methods.

Written as an illustrated, step-by-step guide and workbook for complete beginners, this illustrated, full color book will introduce you to the python programming language using clear explanations, diagrams, coded examples, lab exercises and video demos. You'll begin by learning how to set up the python interpreter and development environment on your computer, then you'll dive straight into the basics of python such as python language syntax, python keywords, and how to write and execute python program. Next, you will learn how to work with python variables, basic data types, arithmetic, companion, and boolean operators. Furthermore, the book covers flow control constructs such as if/else statements and loops in python. You'll also learn how to define and use functions, recursion, and exception handling, as well as a look at the principles of object-oriented programming. You'll also learn how to use turtle graphics to draw various shapes and patterns, and how to build a graphical user interface using tkinter. The last section covers developing a game using the PyGame module and how to add graphics, create basic animations, and user interactivity. At the end of each chapter, you'll find various lab exercises to test what you've learned in the chapter. Also included is a growing repository of sample python source code, bonus material for each chapter, videos, and model solutions to lab exercises to further enhance your learning experience. Absolute Beginner's Python Programming Guide will give you the tools, confidence, and inspiration to start writing Python programs. If you are a beginner, a developer, a student, or someone who wants to learn on their own, this book is for you. What You Will Learn Gain an understanding of computer programming with python Understand different data and data types in python Work with Classes and OOP in python Build interfaces, simple games, and web development with Python This Book Is For beginners developers students anyone who wants to learn Python programming on their own.

For introductory-level Python programming and/or data-science courses. A groundbreaking, flexible approach to computer science and data science The Deitels' Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs), and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science. The book's modular architecture enables instructors to conveniently adapt the text to a wide range of computer-science and data-science courses offered to audiences drawn from many majors. Computer-science instructors can integrate as much or as little data-science and artificial-intelligence topics as they'd like, and data-science instructors can integrate as much or as little Python as they'd like. The book aligns with the latest ACM/IEEE CS-and-related computing curriculum initiatives and with the Data Science Undergraduate Curriculum Proposal sponsored by the National Science Foundation.

This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

Python for Everyone, 1st Edition is a comprehensive introduction to Python and computer programming, which focuses on the principles of programming, software engineering, and effective learning. It is designed for a one-semester, mixed-major, first course in programming. Nobody supports your desire to teach students good programming skills like Cay Horstmann and Rance Necaise. Active in both the classroom and the software industry, Horstmann and Necaise know that meticulous coding—not shortcuts—is the base upon which great programmers are made. Using an innovative visual design that leads students step-by-step through intricacies of Python programming, Python For Everyone, 1st Edition instills confidence in beginning programmers and confidence leads to success.