Search results for "introduction to python programming"
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Python by Example
Python is today's fastest growing programming language. This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader's hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files. This book is perfect for anyone who wants to learn how to program with Python. In particular, students starting out in computer science and teachers who want to improve their confidence in Python will find here a set of ready-made challenges for classroom use.
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How to Write Good Programs
Learning to program isn't just learning the details of a programming language: to become a good programmer you have to become expert at debugging, testing, writing clear code and generally unsticking yourself when you get stuck, while to do well in a programming course you have to learn to score highly in coursework and exams. Featuring tips, stories and explanations of key terms, this book teaches these skills explicitly. Examples in Python, Java and Haskell are included, helping you to gain transferable programming skills whichever language you are learning. Intended for students in Higher or Further Education studying early programming courses, it will help you succeed in, and get the most out of, your course, and support you in developing the software engineering habits that lead to good programs.
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Applying Math with Python
Discover easy-to-follow solutions and techniques to help you to implement applied mathematical concepts such as probability, calculus, and equations using Python's numeric and scientific librariesKey FeaturesCompute complex mathematical problems using programming logic with the help of step-by-step recipesLearn how to use Python libraries for computation, mathematical modeling, and statisticsDiscover simple yet effective techniques for solving mathematical equations and apply them in real-world statisticsBook DescriptionThe updated edition of Applying Math with Python will help you solve complex problems in a wide variety of mathematical fields in simple and efficient ways. Old recipes have been revised for new libraries and several recipes have been added to demonstrate new tools such as JAX.You'll start by refreshing your knowledge of several core mathematical fields and learn about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you progress, you'll gradually get to grips with more advanced topics of calculus, probability, and networks (graph theory). Once you've developed a solid base in these topics, you'll have the confidence to set out on math adventures with Python as you explore Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.What you will learnBecome familiar with basic Python packages, tools, and libraries for solving mathematical problemsExplore real-world applications of mathematics to reduce a problem in optimizationUnderstand the core concepts of applied mathematics and their application in computer scienceFind out how to choose the most suitable package, tool, or technique to solve a problemImplement basic mathematical plotting, change plot styles, and add labels to plots using MatplotlibGet to grips with probability theory with the Bayesian inference and Markov Chain Monte Carlo (MCMC) methodsWho this book is forWhether you are a professional programmer or a student looking to solve mathematical problems computationally using Python, this is the book for you. Advanced mathematics proficiency is not a prerequisite, but basic knowledge of mathematics will help you to get the most out of this Python math book. Familiarity with the concepts of data structures in Python is assumed.
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Introduction to Computer Science
Introduction to Computer Science introduces students to the fundamentals of computer science by connecting the dots between applications they use every day and the underlying technologies that power them. Throughout, students learn valuable technical skills including how to write simple JavaScript programs, format a webpage with HTML and CSS code, reduce the size of a file, and more.Opening chapters of the text provide students with historical background, describe the numbering systems that computers operate with, and explain how computers store and convert data such as images and music. Later chapters explore the anatomy of computer hardware such as CPUs and memory, how computers communicate over networks, and the programming languages that allow us to solve problems using computation. The book concludes with chapters dedicated to security and privacy, the structure and function of operating systems, and the world of e-commerce.Accessible in approach, Introduction to Computer Science is designed to help non-computer science majors learn how technology and computers power the world around them. The text is well suited for introductory courses in computer science.
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Introduction to Bioinformatics and Clinical Scientific Computing
This textbook provides an introduction to computer science theory, informatics best practice, and the standards and legislation that apply to computing in a healthcare environment. It delivers an accessible discussion of databases (construction, interrogation and maintenance); networking (design and low-level application); programming (best practice rather than the specifics of any one language – design, maintenance, safety). It can be used to accompany the NHS Modernising Scientific Careers syllabus. It is also targeted towards those creating software rather than those using it, particularly computer scientists working in healthcare, specifically those in or close to the Physical Sciences, including radiotherapy, nuclear medicine, and equipment management and those working with genomics and health informatics. Features Combines all topics into one comprehensive introduction. Explores practical applications of theory to healthcare. Can be used to accompany the NHS Modernising Scientific Careers syllabus.
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