Search results for "introduction to python programming"
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R 2,926.17
Maya Programming with Python Cookbook
Master complex workflows and conquer the world with Python and MayaAbout This Book• Improve your modelling skills and reduce your scripting problems using Python in Maya• Learn to communicate with web applications using Python for easier team development• A quick and practical answer to every problem you can have whilst scripting in Maya with PythonWho This Book Is ForThis book is for Python developers who have just started scripting with Maya.What You Will Learn• Find out how to use Python scripting to automate tedious tasks• Create functional user interfaces to make scripts easy to share with others• Add new functionality to Maya via the power of scripting• Import and export arbitrary data into and out of Maya• Improve your workflow, and that of your team• Create custom create custom controls to make rigs that are easy to work with• Implement a system to render 3D assets for isometric games• Use script jobs to trigger actions automatically in response to user interaction• Open a command port to allow other applications to communicate with MayaIn DetailMaya is a 3D graphics and animation software, used to develop interactive 3D applications and games with stupendous visual effects. The Maya Programming with Python Cookbook is all about creating fast, powerful automation systems with minimum coding using Maya Python. With the help of insightful and essential recipes, this book will help you improve your modelling skills. Expand your development options and overcome scripting problems encountered whilst developing code in Maya. Right from the beginning, get solutions to complex development concerns faced when implementing as parts of build.Style and approachThis book is comprised of a set of practical recipes, grouped under specific topics, which can be referred to independently or in sequence. These recipes provide quick solutions to common problems, and cover most of the real-world scenarios that developers are likely to face when working with Maya.
R 1,661.00
R 378.00
R 763.00
R 1,369.00
Introduction to C++
This book is primarily for students who are taking a course on the C++ language, for those who wish to self-study the C++ language, and for programmers who have experience with C and want to advance to C++. It could also prove useful to instructors of the C++ course who are looking for explanatory programming examples to add in their lectures. The focus of this book is to provide a solid introduction to the C++ language and programming knowledge through a large number of practical examples and meaningful advice. It includes more than 500 exercises and examples of progressive difficulty to aid the reader in understanding the C++ principles and to see how concepts can materialize in code.The examples are designed to be short, concrete, and substantial, quickly giving the reader the ability to understand how to apply correctly and efficiently the features of the C++ language and to get a solid programming know-how. Rest assured that if you are able to understand this book’s examples and solve the exercises, you can safely go on to edit larger programs, you will be able to develop your own applications, and you will have certainly established a solid fundamental conceptual and practical background to expand your knowledge and skills.
R 8,572.00
Python in Excel for Data Analytics
Learn how to use Python directly in Excel to clean data, build models, and create advanced visualizations. A practical guide for analysts who want to extend Excel without leaving the spreadsheet environment.Key FeaturesUse Python inside Excel for real analytical workflowsBuild visualizations, models, and simulations with easeCombine Excel structure with Python’s analytical powerBook DescriptionExcel is one of the most widely used tools for business analysis, but many analytical tasks quickly reach the limits of formulas and built-in features. Python in Excel changes that by allowing you to perform advanced analysis directly within the spreadsheet environment.This book shows how to combine Excel’s structure and usability with Python’s analytical power. You will learn how to move data between Excel and Python DataFrames, clean and transform datasets efficiently, and explore data using modern visualization techniques.As you progress, you will apply Python to real analytical problems including statistical testing, regression modeling, forecasting, and simulation. You will also learn how to integrate Python outputs into Excel dashboards and reports, creating workflows that are both powerful and practical.Designed for Excel users with no prior programming experience, this book introduces Python concepts gradually and focuses on real-world applications rather than theory. By the end, you will be able to extend Excel in meaningful ways, helping you analyze data more effectively and support better decision-making. What you will learnUse Python directly inside Excel cellsMove data between Excel and DataFramesClean and transform datasets efficientlyBuild advanced visualizations with PythonPerform statistical analysis and modelingForecast trends using time series methodsRun simulations to evaluate uncertaintyCombine Python results with Excel reportsWho this book is forThis book is for business, finance, and operations analysts who rely on Excel and want to go further with their analysis. It is ideal for professionals comfortable with formulas, tables, and PivotTables who want to explore Python without becoming programmers. Early-career data analysts, consultants, and Excel power users will benefit from learning how to extend Excel with more advanced analytical capabilities.
R 1,628.00
Introduction to Assembly Language Programming
This updated textbook introduces readers to assembly and its evolving role in computer programming and design. The author concentrates the revised edition on protected-mode Pentium programming, MIPS assembly language programming, and use of the NASM and SPIM assemblers for a Linux orientation. The focus is on providing students with a firm grasp of the main features of assembly programming, and how it can be used to improve a computer's performance. All of the main features are covered in depth, and the book is equally viable for DOS or Linux, MIPS (RISC) or CISC (Pentium). The book is based on a successful course given by the author and includes numerous hands-on exercises.
R 3,993.00
R 1,008.00
Python GUI Programming Cookbook
Over 80 object-oriented recipes to help you create mind-blowing GUIs in PythonAbout This Book• Use object-oriented programming to develop amazing GUIs in Python• Create a working GUI project as a central resource for developing your Python GUIs• Packed with easy-to-follow recipes to help you develop code using the latest released version of PythonWho This Book Is ForIf you are a Python programmer with intermediate level knowledge of GUI programming and want to learn how to create beautiful, effective, and responsive GUIs using the freely available Python GUI frameworks, this book is for you.What You Will Learn• Create amazing GUIs with Python's built-in Tkinter module• Customize the GUIs by using layout managers to arrange the GUI widgets• Advance to an object-oriented programming style using Python• Develop beautiful charts using the free Matplotlib Python module• Use threading in a networked environment to make the GUIs responsive• Discover ways to connect the GUIs to a database• Understand how unit tests can be created and internationalize the GUI• Extend the GUIs with free Python frameworks using best practices In DetailPython is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a scripting language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Its flexible syntax enables developers to write short scripts while at the same time, they can use object-oriented concepts to develop very large projects.Python GUI Programming Cookbook follows a task-based approach to help you create beautiful and very effective GUIs with the least amount of code necessary. This book uses the simplest programming style, using the fewest lines of code to create a GUI in Python, and then advances to using object-oriented programming in later chapters. If you are new to object-oriented programming (OOP), this book will teach you how to take advantage of the OOP coding style in the context of creating GUIs written in Python.Throughout the book, you will develop an entire GUI application, building recipe upon recipe, connecting the GUI to a database. In the later chapters, you will explore additional Python GUI frameworks, using best practices. You will also learn how to use threading to ensure your GUI doesn't go unresponsive.By the end of the book, you will be an expert in Python GUI programming to develop a common set of GUI applications.Style and approachEvery recipe in this programming cookbook solves a problem you might encounter in your programming career. At the same time, most of the recipes build on each other to create an entire, real-life GUI application.
R 1,661.00
Introduction to Parallel Programming
In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.
R 2,588.30
Introduction to Natural Language Processing Through Prolog
Research into Natural Language Processing - the use of computers to process language - has developed over the last couple of decades into one of the most vigorous and interesting areas of current work on language and communication. This book introduces the subject through the discussion and development of various computer programs which illustrate some of the basic concepts and techniques in the field. The programming language used is Prolog, which is especially well-suited for Natural Language Processing and those with little or no background in computing.Following the general introduction, the first section of the book presents Prolog, and the following chapters illustrate how various Natural Language Processing programs may be written using this programming language. Since it is assumed that the reader has no previous experience in programming, great care is taken to provide a simple yet comprehensive introduction to Prolog. Due to the 'user friendly' nature of Prolog, simple yet effective programs may be written from an early stage. The reader is gradually introduced to various techniques for syntactic processing, ranging from Finite State Network recognisors to Chart parsers. An integral element of the book is the comprehensive set of exercises included in each chapter as a means of cementing the reader's understanding of each topic. Suggested answers are also provided.An Introduction to Natural Language Processing Through Prolog is an excellent introduction to the subject for students of linguistics and computer science, and will be especially useful for those with no background in the subject.
R 7,327.00
Introduction to Linear Programming
Stressing the use of several software packages based on simplex method variations, this text teaches linear programming's four phases through actual practice. It shows how to decide whether LP models should be applied, set up appropriate models, use software to solve them, and examine solutions to a
R 6,684.29
Introduction to C++
This book is primarily for students who are taking a course on the C++ language, for those who wish to self-study the C++ language, and for programmers who have experience with C and want to advance to C++. It could also prove useful to instructors of the C++ course who are looking for explanatory programming examples to add in their lectures. The focus of this book is to provide a solid introduction to the C++ language and programming knowledge through a large number of practical examples and meaningful advice. It includes more than 500 exercises and examples of progressive difficulty to aid the reader in understanding the C++ principles and to see how concepts can materialize in code.The examples are designed to be short, concrete, and substantial, quickly giving the reader the ability to understand how to apply correctly and efficiently the features of the C++ language and to get a solid programming know-how. Rest assured that if you are able to understand this book’s examples and solve the exercises, you can safely go on to edit larger programs, you will be able to develop your own applications, and you will have certainly established a solid fundamental conceptual and practical background to expand your knowledge and skills.
R 2,161.00
Code the Classics Volume II
Take inspiration from the some of the greatest video games of the 1980s and learn how to write your own modern classicsCode the Classics Volume II not only tells the stories of some of the seminal video games of the 1980s, but shows you how to create your own games inspired by them, following examples programmed by Raspberry Pi founder Eben Upton. In this book, you'll learn how to run and edit the games in this book by installing Python, Pygame Zero, and an IDE. You'll also:Get game design tips and tricks from the masters.Understand the fundamental tasks needed for every game: display images, play sound effects and receive inputs from the keyboard or a game controller.Learn how to code your own games with Pygame Zero, a library that helps automate those tasks.Explore the code listings and find out how they work.You'll meet these vintage-inspired games, and learn from their code in between rounds of play:Avenger: fly across a scrolling landscape while you save humans from malevolent aliens.Beat Streets: fight your way through a level, and defeat a notorious crime boss.Eggzy: collect gems and survive as long as possible before time runs out.Leading Edge: Race a car on a pseudo-3d race track.Kinetix: Break bricks with your paddle, and use powerups to avoid various menaces.
R 1,114.00
Scientific Programming and Data Visualization in Mathematical Modeling
This book is a practical guide introducing the MATLAB and Python programming languages and their capabilities. It provides real-world examples and exercises to demonstrate Python's practical applications in contrast to MATLAB's.The book follows a sequential learning approach, starting with the coverage of mathematical concepts using MATLAB, and then transitioning to Python. This approach aims to bridge the gap in developing numerical programs in both languages, ensuring a smooth learning experience.Additionally, the book covers Symbolic computation techniques required in various analytic mathematical models using both MATLAB and Python.This book is ideal for mathematics students, researchers who need to incorporate mathematical programming in allied disciplines, data science specialists interested in MATLAB and Python numerical techniques.The main highlights of the proposed work are:• How to solve ordinary differential equations via MATLAB and Python• Dealing with a variety of partial differential equations through MATLAB and Python• Symbolic computation via MATLAB and Python• Data visualization through MATLAB and Python in a comparative mode.
R 2,143.00
Introduction to Data Science for Social and Policy Research
Real-world data sets are messy and complicated. Written for students in social science and public management, this authoritative but approachable guide describes all the tools needed to collect data and prepare it for analysis. Offering detailed, step-by-step instructions, it covers collection of many different types of data including web files, APIs, and maps; data cleaning; data formatting; the integration of different sources into a comprehensive data set; and storage using third-party tools to facilitate access and shareability, from Google Docs to GitHub. Assuming no prior knowledge of R and Python, the author introduces programming concepts gradually, using real data sets that provide the reader with practical, functional experience.
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R 854.00
Introduction to Scientific Programming and Simulation Using R
Learn How to Program Stochastic ModelsHighly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce scientific programming and stochastic modelling in a clear, practical, and thorough way. Readers learn programming by experimenting with the provided R code and data.The book’s four parts teach: Core knowledge of R and programming conceptsHow to think about mathematics from a numerical point of view, including the application of these concepts to root finding, numerical integration, and optimisationEssentials of probability, random variables, and expectation required to understand simulationStochastic modelling and simulation, including random number generation and Monte Carlo integration In a new chapter on systems of ordinary differential equations (ODEs), the authors cover the Euler, midpoint, and fourth-order Runge-Kutta (RK4) schemes for solving systems of first-order ODEs. They compare the numerical efficiency of the different schemes experimentally and show how to improve the RK4 scheme by using an adaptive step size. Another new chapter focuses on both discrete- and continuous-time Markov chains. It describes transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It also presents methods for simulating discrete- and continuous-time chains as well as techniques for defining the state space, including lumping states and supplementary variables.Building readers’ statistical intuition, Introduction to Scientific Programming and Simulation Using R, Second Edition shows how to turn algorithms into code. It is designed for those who want to make tools, not just use them. The code and data are available for download from CRAN.
R 5,694.76
Introduction to Optimization with Applications in Machine Learning and Data Analytics
The primary goal of this text is a practical one. Equipping students with the enough knowledge and creating an independent research platform, the author strives to prepare students for professional careers. Providing students with a marketable skill set requires topics from many areas of optimization. The initial goal of this text is to develop a marketable skill set for mathematics majors but also for students of engineering, computer science, economics, statistics, and business. Optimization reaches into many different fields.This text provides a balance where one is needed. Mathematics optimization books are often too heavy on theory without enough applications; texts aimed at business students are often strong on applications, but weak on math. The book represents an attempt at overcoming this imbalance for all students taking such a course.The book contains many practical applications but also explains the mathematics behind the techniques, including stating definitions and proving theorems. Optimization techniques are at the heart of the first spam filters, are used in self-driving cars, play a great role in machine learning, and can be used in such places as determining a batting order in a Major League Baseball game. Additionally, it has seemingly limitless other applications in business and industry.Many of the problems rely on using a computer. Microsoft’s Excel is most often used as this is common in business, but Python and other languages are considered. The consideration of other programming languages permits experienced mathematics and engineering students to use MATLAB or Mathematica or computer science students to write their own programs in Java or Python.
R 5,673.15
Introduction to Network Programming with Java
Since the second edition of this text, the use of the Internet and networks generally has continued to expand at a phenomenal rate. This has led to both an increase in demand for network software and to improvements in the technology used to run such networks, with the latter naturally leading to changes in the former. During this time, the Java libraries have been updated to keep up with the new developments in network technology, so that the Java programming language continues to be one of the mainstays of network software development.In providing a very readable text that avoids getting immersed in low-level technical details, while still providing a useful, practical guide to network programming for both undergraduates and busy IT professionals, this third edition continues the trend of its predecessors. To retain its currency, the text has been updated to reflect changes that have taken place in Java's network technology over the past seven years (including the release of Java 7), whilst retaining its notable features of numerous code examples, screenshots and end-of-chapter exercises.
R 1,571.51
R 1,310.00
Qt5 Python GUI Programming Cookbook
Over 60 recipes to help you design interactive, smart, and cross-platform GUI applicationsKey Features Get succinct QT solutions to pressing GUI programming problems in Python Learn how to effectively implement reactive programming Build customized applications that are robust and reliableBook DescriptionPyQt is one of the best cross-platform interface toolkits currently available; it's stable, mature, and completely native. If you want control over all aspects of UI elements, PyQt is what you need. This book will guide you through every concept necessary to create fully functional GUI applications using PyQt, with only a few lines of code.As you expand your GUI using more widgets, you will cover networks, databases, and graphical libraries that greatly enhance its functionality. Next, the book guides you in using Qt Designer to design user interfaces and implementing and testing dialogs, events, the clipboard, and drag and drop functionality to customize your GUI. You will learn a variety of topics, such as look and feel customization, GUI animation, graphics rendering, implementing Google Maps, and more. Lastly, the book takes you through how Qt5 can help you to create cross-platform apps that are compatible with Android and iOS. You will be able to develop functional and appealing software using PyQt through interesting and fun recipes that will expand your knowledge of GUIsWhat you will learn Use basic Qt components, such as a radio button, combo box, and sliders Use QSpinBox and sliders to handle different signals generated on mouse clicks Work with different Qt layouts to meet user interface requirements Create custom widgets and set up customizations in your GUI Perform asynchronous I/O operations and thread handling in the Python GUI Employ network concepts, internet browsing, and Google Maps in UI Use graphics rendering and implement animation in your GUI Make your GUI application compatible with Android and iOS devicesWho this book is forIf you’re an intermediate Python programmer wishing to enhance your coding skills by writing powerful GUIs in Python using PyQT, this is the book for you.
R 1,889.00
R 977.00
Beginner's Guide to Scala, Object Orientation and Functional Programming
Scala is now an established programming language developed by Martin Oderskey and his team at the EPFL. The name Scala is derived from Sca(lable) La(nguage). Scala is a multi-paradigm language, incorporating object oriented approaches with functional programming. Although some familiarity with standard computing concepts is assumed (such as the idea of compiling a program and executing this compiled from etc.) and with basic procedural language concepts (such as variables and allocation of values to these variables) the early chapters of the book do not assume any familiarity with object orientation nor with functional programming These chapters also step through other concepts with which the reader may not be familiar (such as list processing). From this background, the book provides a practical introduction to both object and functional approaches using Scala. These concepts are introduced through practical experience taking the reader beyond the level of the language syntax to the philosophy and practice of object oriented development and functional programming. Students and those actively involved in the software industry will find this comprehensive introduction to Scala invaluable.
R 2,564.00
Python for AI, Machine Learning, and Deep Learning
Learn AI, machine learning, and deep learning with Python from the ground up, then build and tune models with XGBoost, TensorFlow, PyTorch, CNNs, RNNs, transformers, and transfer learning through practical Python projects.Key FeaturesBuild Python, data science, mathematics, and statistics foundations for machine learningTrain, evaluate, and tune regression, classification, ensemble, XGBoost, LightGBM, and CatBoost modelsCreate CNN, RNN, transformer, and transfer learning projects with TensorFlow, Keras, and PyTorchBook DescriptionLearning modern AI often feels fragmented: Python in one resource, mathematics in another, and deep learning or transformers somewhere else. This book brings those foundations into one practical progression, helping you connect the concepts behind machine learning with the code used to build models.You will start with Python programming, NumPy, Pandas, data visualization, exploratory data analysis, linear algebra, calculus, probability, and statistics. From there, you will build supervised learning skills across regression, classification, k-NN, feature engineering, model evaluation, cross-validation, and hyperparameter tuning. You will then work with ensemble methods including random forests, gradient boosting, XGBoost, LightGBM, and CatBoost, while learning to handle imbalanced data and justify modeling decisions.The final part moves into neural networks and deep learning with TensorFlow, Keras, and PyTorch. You will build CNNs for image classification, explore RNNs, LSTMs, GRUs, word embeddings, and sequence-to-sequence models, and understand attention and transformer architectures through BERT and GPT examples. You will finish by applying transfer learning and fine-tuning to computer vision and NLP tasks, supported by projects that turn theory into practical AI and machine learning skills for real-world problem solving.What you will learnUse Python, NumPy, Pandas, Matplotlib, and Seaborn for data analysisApply linear algebra, calculus, probability, and statistics to MLBuild regression, classification, and k-NN modelsEngineer features and evaluate models with cross-validation and hyperparameter tuningTrain ensembles with random forests, XGBoost, LightGBM, and CatBoostBuild neural networks and CNNs with TensorFlow, Keras, and PyTorchDevelop RNNs, LSTMs, GRUs, attention, BERT, and GPT workflows for NLPApply transfer learning and fine-tuning to computer vision and NLPWho this book is forThis book is for aspiring data scientists, machine learning engineers, AI developers, students, and career changers who want one structured path from Python fundamentals to machine learning and deep learning. It suits readers seeking practical skills in data analysis, predictive modeling, computer vision, NLP, transformers, and transfer learning. No prior machine learning or deep learning experience is required. Python is introduced from the fundamentals, although basic programming familiarity and foundational mathematics will help.
R 1,628.00
R 1,464.00
Gamer's Introduction to Programming with MonoGame
A Gamer’s Introduction to Programming with MonoGame: Welcome Brave Adventurer! is a great way to combine your current love of both video games and coding into a brand‑new love of writing your own games. In this book, you’ll learn the essential ins‑and‑outs of how to work with fonts and text, images and sprites, audio, and even animation. You’ll learn how to give your players control over their destiny through keyboards, mice, and gamepads, and you’ll harness the never‑ending energy of the gameplay loop functions. But coding books are technical, boring, and scary, aren’t they? Not this one. Within these pages, you’ll find a fun and approachable adventure that will introduce you to the accessible but powerful MonoGame development framework. Using Visual Studio and C#, you’ll write simple but engaging interactive scenes and games that will gradually build up your coding skills and confidence. Packed with practical examples, plain‑language explanations, images, and illustrations, this book is structured like a video game, complete with levels to progress through, cutscenes to give you extra information, and final challenge projects to show you how everything fits together and to help build your own creative portfolio. It is also the second book in an ongoing series designed to take you from zero experience to writing your own video games and interactive digital experiences using industry standard languages and tools. For readers with previous object‑oriented programming experience, this book is a standalone introductory MonoGame adventure. Gain even more experience by exploring the resources, bonus materials, and extensive code samples available at the companion website: https://welcomebraveadventurer.ca. Now, gather your courage and prepare to level up by joining the MonoGame coding quests that await you inside.
R 2,966.97
R 305.00
Tutorial Introduction to VHDL Programming
This book helps readers create good VHDL descriptions and simulate VHDL designs. It teaches VHDL using selected sample problems, which are solved step by step and with precise explanations, so that readers get a clear idea of what a good VHDL code should look like.The book is divided into eight chapters, covering aspects ranging from the very basics of VHDL syntax and the module concept, to VHDL logic circuit implementations. In the first chapter, the entity and architecture parts of a VHDL program are explained in detail. The second chapter explains the implementations of combinational logic circuits in VHDL language, while the following chapters offer information on the simulation of VHDL programs and demonstrate how to define data types other than the standard ones available in VHDL libraries. In turn, the fifth chapter explains the implementation of clocked sequential logic circuits, and the sixth shows the implementation of registers and counter packages. The book’s last two chapters detail how components, functions and procedures, as well as floating-point numbers, are implemented in VHDL. The book offers extensive exercises at the end of each chapter, inviting readers to learn VHDL by doing it and writing good code.
R 2,665.52
Introduction to Assembly Language Programming
This updated textbook introduces readers to assembly and its evolving role in computer programming and design. The author concentrates the revised edition on protected-mode Pentium programming, MIPS assembly language programming, and use of the NASM and SPIM assemblers for a Linux orientation. The focus is on providing students with a firm grasp of the main features of assembly programming, and how it can be used to improve a computer's performance. All of the main features are covered in depth, and the book is equally viable for DOS or Linux, MIPS (RISC) or CISC (Pentium). The book is based on a successful course given by the author and includes numerous hands-on exercises.
R 2,909.91
Introduction to Reliable and Secure Distributed Programming
In modern computing a program is usually distributed among several processes. The fundamental challenge when developing reliable and secure distributed programs is to support the cooperation of processes required to execute a common task, even when some of these processes fail. Failures may range from crashes to adversarial attacks by malicious processes.Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks. The authors follow an incremental approach by first introducing basic abstractions in simple distributed environments, before moving to more sophisticated abstractions and more challenging environments. Each core chapter is devoted to one topic, covering reliable broadcast, shared memory, consensus, and extensions of consensus. For every topic, many exercises and their solutions enhance the understanding This book represents the second edition of "Introduction to Reliable Distributed Programming". Its scope has been extended to include security against malicious actions by non-cooperating processes. This important domain has become widely known under the name "Byzantine fault-tolerance".
R 3,142.12
R 455.00
Introduction to College Mathematics with A Programming Language
The topics covered in this text are those usually covered in a full year's course in finite mathematics or mathematics for liberal arts students. They correspond very closely to the topics I have taught at Western New England College to freshmen business and liberal arts students. They include set theory, logic, matrices and determinants, functions and graph ing, basic differential and integral calculus, probability and statistics, and trigonometry. Because this is an introductory text, none of these topics is dealt with in great depth. The idea is to introduce the student to some of the basic concepts in mathematics along with some of their applications. I believe that this text is self-contained and can be used successfully by any college student who has completed at least two years of high school mathematics including one year of algebra. In addition, no previous knowledge of any programming language is necessary. The distinguishing feature of this text is that the student is given the opportunity to learn the mathematical concepts via A Programming Lan guage (APL). APL was developed by Kenneth E. Iverson while he was at Harvard University and was presented in a book by Dr. Iverson entitled A i Programming Language in 1962. He invented APL for educational purpo ses. That is, APL was designed to be a consistent, unambiguous, and powerful notation for communicating mathematical ideas. In 1966, APL became available on a time-sharing system at IBM.
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R 1,191.00
