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| computer science foundation course: Foundations of Computer Science Behrouz A. Forouzan, 2008 |
| computer science foundation course: Foundations of Computer Science Alfred V. Aho, Jeffrey D. Ullman, 1994-10-15 |
| computer science foundation course: Foundations for Programming Languages John C. Mitchell, 1996 Programming languages embody the pragmatics of designing software systems, and also the mathematical concepts which underlie them. Anyone who wants to know how, for example, object-oriented programming rests upon a firm foundation in logic should read this book. It guides one surefootedly through the rich variety of basic programming concepts developed over the past forty years. -- Robin Milner, Professor of Computer Science, The Computer Laboratory, Cambridge University Programming languages need not be designed in an intellectual vacuum; John Mitchell's book provides an extensive analysis of the fundamental notions underlying programming constructs. A basic grasp of this material is essential for the understanding, comparative analysis, and design of programming languages. -- Luca Cardelli, Digital Equipment Corporation Written for advanced undergraduate and beginning graduate students, Foundations for Programming Languages uses a series of typed lambda calculi to study the axiomatic, operational, and denotational semantics of sequential programming languages. Later chapters are devoted to progressively more sophisticated type systems. |
| computer science foundation course: Foundation Mathematics for Computer Science John Vince, 2015-07-27 John Vince describes a range of mathematical topics to provide a foundation for an undergraduate course in computer science, starting with a review of number systems and their relevance to digital computers, and finishing with differential and integral calculus. Readers will find that the author's visual approach will greatly improve their understanding as to why certain mathematical structures exist, together with how they are used in real-world applications. Each chapter includes full-colour illustrations to clarify the mathematical descriptions, and in some cases, equations are also coloured to reveal vital algebraic patterns. The numerous worked examples will consolidate comprehension of abstract mathematical concepts. Foundation Mathematics for Computer Science covers number systems, algebra, logic, trigonometry, coordinate systems, determinants, vectors, matrices, geometric matrix transforms, differential and integral calculus, and reveals the names of the mathematicians behind such inventions. During this journey, John Vince touches upon more esoteric topics such as quaternions, octonions, Grassmann algebra, Barycentric coordinates, transfinite sets and prime numbers. Whether you intend to pursue a career in programming, scientific visualisation, systems design, or real-time computing, you should find the author’s literary style refreshingly lucid and engaging, and prepare you for more advanced texts. |
| computer science foundation course: Foundations of Computation Carol Critchlow, David Eck, 2011 Foundations of Computation is a free textbook for a one-semester course in theoretical computer science. It has been used for several years in a course at Hobart and William Smith Colleges. The course has no prerequisites other than introductory computer programming. The first half of the course covers material on logic, sets, and functions that would often be taught in a course in discrete mathematics. The second part covers material on automata, formal languages and grammar that would ordinarily be encountered in an upper level course in theoretical computer science. |
| computer science foundation course: Discrete Mathematics and Computing Malik Magdon-Ismail, 2019-12-14 This text is a semester course in the basic mathematical and theoretical foundations of computer science. Students who make heavy use of computing should learn these foundations well, setting a base for a follow-on course in algorithms. A solid theoretical and algorithmic foundation in computer science sets the stage for developing good programs, programs that work, always and efficiently.Each chapter is a lecture that has been taught as such. Part I starts with basic logic, proofs and discrete mathematics, including: induction, recursion, summation, asymptotics and number theory. We then continue with graphs, counting and combinatorics, and wrap up the coverage of discrete mathematics with discrete probability. Part II presents the blockbuster application of discrete mathematics: the digital computer and a theory of computing. The goal is to understand what a computer can and cannot do. We start small, with automata, and end big with Turing Machines.Our approach is Socratic. The reader is encouraged to participate actively in the learning process by doing the quizzes and exercises that are liberally sprinkled through the text. The pace and level is appropriate for readers with one year of training in programming and calculus (college sophomores). |
| computer science foundation course: Understanding by Design Grant P. Wiggins, Jay McTighe, 2005 What is understanding and how does it differ from knowledge? How can we determine the big ideas worth understanding? Why is understanding an important teaching goal, and how do we know when students have attained it? How can we create a rigorous and engaging curriculum that focuses on understanding and leads to improved student performance in today's high-stakes, standards-based environment? Authors Grant Wiggins and Jay McTighe answer these and many other questions in this second edition of Understanding by Design. Drawing on feedback from thousands of educators around the world who have used the UbD framework since its introduction in 1998, the authors have greatly revised and expanded their original work to guide educators across the K-16 spectrum in the design of curriculum, assessment, and instruction. With an improved UbD Template at its core, the book explains the rationale of backward design and explores in greater depth the meaning of such key ideas as essential questions and transfer tasks. Readers will learn why the familiar coverage- and activity-based approaches to curriculum design fall short, and how a focus on the six facets of understanding can enrich student learning. With an expanded array of practical strategies, tools, and examples from all subject areas, the book demonstrates how the research-based principles of Understanding by Design apply to district frameworks as well as to individual units of curriculum. Combining provocative ideas, thoughtful analysis, and tested approaches, this new edition of Understanding by Design offers teacher-designers a clear path to the creation of curriculum that ensures better learning and a more stimulating experience for students and teachers alike. |
| computer science foundation course: Mathematics for Computer Science Eric Lehman, F. Thomson Leighton, Albert R. Meyer, 2017-03-08 This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions. |
| computer science foundation course: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| computer science foundation course: Concrete Mathematics Ronald L. Graham, Donald E. Knuth, Oren Patashnik, 1994-02-28 This book introduces the mathematics that supports advanced computer programming and the analysis of algorithms. The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data. It is an indispensable text and reference not only for computer scientists - the authors themselves rely heavily on it! - but for serious users of mathematics in virtually every discipline. Concrete Mathematics is a blending of CONtinuous and disCRETE mathematics. More concretely, the authors explain, it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems. The subject matter is primarily an expansion of the Mathematical Preliminaries section in Knuth's classic Art of Computer Programming, but the style of presentation is more leisurely, and individual topics are covered more deeply. Several new topics have been added, and the most significant ideas have been traced to their historical roots. The book includes more than 500 exercises, divided into six categories. Complete answers are provided for all exercises, except research problems, making the book particularly valuable for self-study. Major topics include: Sums Recurrences Integer functions Elementary number theory Binomial coefficients Generating functions Discrete probability Asymptotic methods This second edition includes important new material about mechanical summation. In response to the widespread use of the first edition as a reference book, the bibliography and index have also been expanded, and additional nontrivial improvements can be found on almost every page. Readers will appreciate the informal style of Concrete Mathematics. Particularly enjoyable are the marginal graffiti contributed by students who have taken courses based on this material. The authors want to convey not only the importance of the techniques presented, but some of the fun in learning and using them. |
| computer science foundation course: Foundations of Data Science Avrim Blum, John Hopcroft, Ravindran Kannan, 2020-01-23 This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. |
| computer science foundation course: Structure and Interpretation of Computer Programs Harold Abelson, Gerald Jay Sussman, 2022-05-03 A new version of the classic and widely used text adapted for the JavaScript programming language. Since the publication of its first edition in 1984 and its second edition in 1996, Structure and Interpretation of Computer Programs (SICP) has influenced computer science curricula around the world. Widely adopted as a textbook, the book has its origins in a popular entry-level computer science course taught by Harold Abelson and Gerald Jay Sussman at MIT. SICP introduces the reader to central ideas of computation by establishing a series of mental models for computation. Earlier editions used the programming language Scheme in their program examples. This new version of the second edition has been adapted for JavaScript. The first three chapters of SICP cover programming concepts that are common to all modern high-level programming languages. Chapters four and five, which used Scheme to formulate language processors for Scheme, required significant revision. Chapter four offers new material, in particular an introduction to the notion of program parsing. The evaluator and compiler in chapter five introduce a subtle stack discipline to support return statements (a prominent feature of statement-oriented languages) without sacrificing tail recursion. The JavaScript programs included in the book run in any implementation of the language that complies with the ECMAScript 2020 specification, using the JavaScript package sicp provided by the MIT Press website. |
| computer science foundation course: Stuck in the Shallow End, updated edition Jane Margolis, 2017-03-03 Why so few African American and Latino/a students study computer science: updated edition of a book that reveals the dynamics of inequality in American schools. The number of African Americans and Latino/as receiving undergraduate and advanced degrees in computer science is disproportionately low. And relatively few African American and Latino/a high school students receive the kind of institutional encouragement, educational opportunities, and preparation needed for them to choose computer science as a field of study and profession. In Stuck in the Shallow End, Jane Margolis and coauthors look at the daily experiences of students and teachers in three Los Angeles public high schools: an overcrowded urban high school, a math and science magnet school, and a well-funded school in an affluent neighborhood. They find an insidious “virtual segregation” that maintains inequality. The race gap in computer science, Margolis discovers, is one example of the way students of color are denied a wide range of occupational and educational futures. Stuck in the Shallow End is a story of how inequality is reproduced in America—and how students and teachers, given the necessary tools, can change the system. Since the 2008 publication of Stuck in the Shallow End, the book has found an eager audience among teachers, school administrators, and academics. This updated edition offers a new preface detailing the progress in making computer science accessible to all, a new postscript, and discussion questions (coauthored by Jane Margolis and Joanna Goode). |
| computer science foundation course: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| computer science foundation course: The Elements of Computing Systems Noam Nisan, Shimon Schocken, 2008 This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system. |
| computer science foundation course: Foundation Course for Advanced Computer Studies Franck Ismael Djédjé, 2015-11-13 In the modern world, computer systems are playing a greater and greater part in everyday life. From office work, to entertainment, to providing information, the personal computer is quickly becoming a more integral part of the home. However, most PC users have no idea how most of the parts which make up their computer work internally. I am one of those who find that the framework provided by the school curriculum in the United Kingdom is of great assistance in planning lessons and learning plans but the curriculum does not plan out the work for us. We therefore need to invest a lot of time and effort into developing schemes of work that will suit the people we are going to teach. For me, it is a fantastic opportunity to employ our imagination and creativity to make lessons useful and interesting for children of different abilities. It is why I wrote this book. This book is a foundation course for Advanced Computer Studies and designed as a blueprint to teach users with a basic knowledge of computer science. Computer science is a subject that combines the use of technology which is ICT (Information Communication Technology) and the creation of technology. To use ICT (the subject about how to use technology to communicate information) more effectively, we need to know how technology works. Computing or computer science will create a generation of young people able to work at the forefront of technology change. It is the umbrella term for the subject that comprises 3 elements: computer science, information technology and digital literacy. It is helpful to think of these as the foundations, applications and implications of digital technology. The new focus on computer science will provides a well-defined and rigorous academic discipline and a unique lens through which pupils can understand the world. Children must therefore be taught computing if they are to be ready for tomorrow technology challenges. Our ingenuity to invent new means of communicating with each other, our very human compulsion to communicate have driven the technological innovations of the past two centuries however still a lot remain to be done with the arrival of quantum computing. A more rigorous approach to computer science teaching will help compete across the full spectrum of digital industries. This can only be achieved by equipping ourselves with the foundation skills, knowledge and understanding of computing do the necessity to introduce “computational thinking” at school via the new national curriculum (programmes of study and targets), the 2014 national curriculum that introduces computing which will replace ICT. |
| computer science foundation course: Foundations of Machine Learning, second edition Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar, 2018-12-25 A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these algorithms. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning is unique in its focus on the analysis and theory of algorithms. The first four chapters lay the theoretical foundation for what follows; subsequent chapters are mostly self-contained. Topics covered include the Probably Approximately Correct (PAC) learning framework; generalization bounds based on Rademacher complexity and VC-dimension; Support Vector Machines (SVMs); kernel methods; boosting; on-line learning; multi-class classification; ranking; regression; algorithmic stability; dimensionality reduction; learning automata and languages; and reinforcement learning. Each chapter ends with a set of exercises. Appendixes provide additional material including concise probability review. This second edition offers three new chapters, on model selection, maximum entropy models, and conditional entropy models. New material in the appendixes includes a major section on Fenchel duality, expanded coverage of concentration inequalities, and an entirely new entry on information theory. More than half of the exercises are new to this edition. |
| computer science foundation course: Elements of Robotics Mordechai Ben-Ari, Francesco Mondada, 2017-10-25 This open access book bridges the gap between playing with robots in school and studying robotics at the upper undergraduate and graduate levels to prepare for careers in industry and research. Robotic algorithms are presented formally, but using only mathematics known by high-school and first-year college students, such as calculus, matrices and probability. Concepts and algorithms are explained through detailed diagrams and calculations. Elements of Robotics presents an overview of different types of robots and the components used to build robots, but focuses on robotic algorithms: simple algorithms like odometry and feedback control, as well as algorithms for advanced topics like localization, mapping, image processing, machine learning and swarm robotics. These algorithms are demonstrated in simplified contexts that enable detailed computations to be performed and feasible activities to be posed. Students who study these simplified demonstrations will be well prepared for advanced study of robotics. The algorithms are presented at a relatively abstract level, not tied to any specific robot. Instead a generic robot is defined that uses elements common to most educational robots: differential drive with two motors, proximity sensors and some method of displaying output to the user. The theory is supplemented with over 100 activities, most of which can be successfully implemented using inexpensive educational robots. Activities that require more computation can be programmed on a computer. Archives are available with suggested implementations for the Thymio robot and standalone programs in Python. |
| computer science foundation course: Ultralearning Scott H. Young, 2019-08-06 Now a Wall Street Journal bestseller. Learn a new talent, stay relevant, reinvent yourself, and adapt to whatever the workplace throws your way. Ultralearning offers nine principles to master hard skills quickly. This is the essential guide to future-proof your career and maximize your competitive advantage through self-education. In these tumultuous times of economic and technological change, staying ahead depends on continual self-education—a lifelong mastery of fresh ideas, subjects, and skills. If you want to accomplish more and stand apart from everyone else, you need to become an ultralearner. The challenge of learning new skills is that you think you already know how best to learn, as you did as a student, so you rerun old routines and old ways of solving problems. To counter that, Ultralearning offers powerful strategies to break you out of those mental ruts and introduces new training methods to help you push through to higher levels of retention. Scott H. Young incorporates the latest research about the most effective learning methods and the stories of other ultralearners like himself—among them Benjamin Franklin, chess grandmaster Judit Polgár, and Nobel laureate physicist Richard Feynman, as well as a host of others, such as little-known modern polymath Nigel Richards, who won the French World Scrabble Championship—without knowing French. Young documents the methods he and others have used to acquire knowledge and shows that, far from being an obscure skill limited to aggressive autodidacts, ultralearning is a powerful tool anyone can use to improve their career, studies, and life. Ultralearning explores this fascinating subculture, shares a proven framework for a successful ultralearning project, and offers insights into how you can organize and exe - cute a plan to learn anything deeply and quickly, without teachers or budget-busting tuition costs. Whether the goal is to be fluent in a language (or ten languages), earn the equivalent of a college degree in a fraction of the time, or master multiple tools to build a product or business from the ground up, the principles in Ultralearning will guide you to success. |
| computer science foundation course: Computer Science Handbook Allen B. Tucker, 2004-06-28 When you think about how far and fast computer science has progressed in recent years, it's not hard to conclude that a seven-year old handbook may fall a little short of the kind of reference today's computer scientists, software engineers, and IT professionals need. With a broadened scope, more emphasis on applied computing, and more than 70 chap |
| computer science foundation course: Computer Science and Education Wenxing Hong, Yang Weng, 2023-06-16 This three-volume set constitues selected papers presented during the 17th International Conference on Computer Science and Education, ICCSE 2022, held in Ningbo, China, in August 2022. The 168 full papers and 43 short papers presented were thoroughly reviewed and selected from the 510 submissions. They focus on a wide range of computer science topics, especially AI, data science, and engineering, and technology-based education, by addressing frontier technical and business issues essential to the applications of data science in both higher education and advancing e-Society. |
| computer science foundation course: AP® Computer Science Principles Crash Course Jacqueline Corricelli, 2018-01-04 AP® Computer Science Principles Crash Course® A Higher Score in Less Time! REA's AP® Computer Science Principles Crash Course® is the top choice for the last-minute studier or any Computer Science Principles student who wants a quick refresher on the course. Are you crunched for time? Have you started studying for your Advanced Placement® Computer Science Principles exam yet? How will you memorize everything you need to know before the test? Do you wish there was a fast and easy way to study for the exam AND boost your score? If this sounds like you, don't panic. REA's Crash Course for AP® Computer Science Principles is just what you need. Our Crash Course gives you: Targeted Review - Study Only What You Need to Know. The review is based on an in-depth analysis of the AP® Computer Science Principles course description outline and sample AP® test questions. It covers only the information tested on the exam, so you can make the most of your valuable study time. Expert Test-taking Strategies and Advice. Written by Jacqueline Corricelli, an award-winning AP® Computer Science Principles teacher and test development expert, the book gives you the topics and critical context that will matter most on exam day. Crash Course® relies on the author’s extensive analysis of the test’s structure and content. By following her advice, you can boost your score. REA's Online Practice Exam. Are you ready for your exam? Take REA's practice exam and find out. You'll get the benefits of timed testing, detailed explanations of answers, and automatic scoring analysis. Our practice exam is balanced to include every topic and type of question found on the actual AP® exam, so you'll be confident on test day. Whether you're cramming for the exam or reinforcing what you learn as you go through the course, this is the study guide every AP® Computer Science Principles student must have. |
| computer science foundation course: Fundamental Concepts in Computer Science Erol Gelenbe, 2009 This book presents fundamental contributions to computer science as written and recounted by those who made the contributions themselves. As such, it is a highly original approach to a OC living historyOCO of the field of computer science. The scope of the book is broad in that it covers all aspects of computer science, going from the theory of computation, the theory of programming, and the theory of computer system performance, all the way to computer hardware and to major numerical applications of computers. |
| computer science foundation course: Future Communication, Information and Computer Science Dawei Zheng, 2015-02-05 The 2014 International Conference on Future Communication, Information and Computer Science (FCICS 2014) was held May 22-23, 2014 in Beijing, China. The objective of FCICS 2014 was to provide a platform for researchers, engineers and academics as well as industrial professionals from all over the world to present their research results and development activities in Computer, Network and Information Technology and Communication Engineering. |
| computer science foundation course: Computation Structures Stephen A. Ward, Robert H. Halstead, 1990 Computer Systems Organization -- general. |
| computer science foundation course: Competing in the Age of AI Marco Iansiti, Karim R. Lakhani, 2020-01-07 a provocative new book — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how collisions between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI. |
| computer science foundation course: Computer Science Principles Kevin Hare, 2022-04 |
| computer science foundation course: Computer, Intelligent Computing and Education Technology Hsiang-Chuan Liu, Wen-Pei Sung, Wenli Yao, 2014-03-26 This proceedings set contains selected Computer, Information and Education Technology related papers from the 2014 International Conference on Computer, Intelligent Computing and Education Technology (CICET 2014), held March 27-28, 2014 in Hong Kong. The proceedings aims to provide a platform for researchers, engineers and academics as well as industry professionals from all over the world to present their research results and development activities in Computer Science, Information Technology and Education Technology. |
| computer science foundation course: Limits of Computation Bernhard Reus, 2016-03-25 This textbook discusses the most fundamental and puzzling questions about the foundations of computing. In 23 lecture-sized chapters it provides an exciting tour through the most important results in the field of computability and time complexity, including the Halting Problem, Rice's Theorem, Kleene's Recursion Theorem, the Church-Turing Thesis, Hierarchy Theorems, and Cook-Levin's Theorem. Each chapter contains classroom-tested material, including examples and exercises. Links between adjacent chapters provide a coherent narrative. Fundamental results are explained lucidly by means of programs written in a simple, high-level imperative programming language, which only requires basic mathematical knowledge. Throughout the book, the impact of the presented results on the entire field of computer science is emphasised. Examples range from program analysis to networking, from database programming to popular games and puzzles. Numerous biographical footnotes about the famous scientists who developed the subject are also included. Limits of Computation offers a thorough, yet accessible, introduction to computability and complexity for the computer science student of the 21st century. |
| computer science foundation course: Python for Everybody Charles R. Severance, 2016-04-09 Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled Python for Informatics: Exploring Information.There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course. |
| computer science foundation course: Operating Systems Remzi H. Arpaci-Dusseau, Andrea C. Arpaci-Dusseau, 2018-09 This book is organized around three concepts fundamental to OS construction: virtualization (of CPU and memory), concurrency (locks and condition variables), and persistence (disks, RAIDS, and file systems--Back cover. |
| computer science foundation course: Saucer Wisdom Rudy Rucker, 2001-07-13 Brace yourself when you open this book, for it purports to be the about the visions of neat biotechnologies one Frank Shook brings back from future times where he has been taken to by flying saucers, and gives to the writer, Rudy Rucker, who's telling the story. That's an odd way to begin a work of popular science . . . . but amusing. Please heed the warning from the Introduction by Bruce Sterling: If you are examining Saucer Wisdom imagining that Rudy (or some fictional 'Frank Shook') has been actually logging a lot of on board saucer time, well, you can knock that off right now. Rudy Rucker made up the flying saucer part. There is no actual flying saucer. The saucer is not an interplanetary faster-than-light device. Its what we professional authors like to call a narrative device. I'm going to spill the beans as directly as I can here: Saucer Wisdom is a work of popular science speculation. Its a nonfiction book in which Prof. Rucker takes a few quirky grains of modern scientific fact, drops them into the colorful tide pool of his own imagination, and harvests a major swarm of abalones, jellyfish, and giant anemones. Pop-science writers didn't used to treat 'science' in this boisterous way, but there might well be a trend here, there may be a real future in this. Saucer Wisdom is a book by a well-qualified mathematician and computer scientist, a veteran pop science writer, in which 'science' is treated, not as some distant and rarefied quest for absolute knowledge, but as naturally great source material for a really long, cool rant. Rucker, in character, describes, and illustrates with delightful cartoon sketches (the way he would use chalk and a blackboard while talking science), the world of the progressively more distant future as it is transformed by computer technology, biotechnology, and human evolution. He also describes a hell of a party in Berkeley. Popular science writing will never be the same. At the publisher's request, this title is being sold without Digital Rights Management software (DRM) applied. |
| computer science foundation course: A Guide to Undergraduate Science Course and Laboratory Improvements National Science Foundation (U.S.). Directorate for Science Education, 1979 |
| computer science foundation course: The Hacker and the Ants Rudy Rucker, 2009-07-21 This cyberpunk adventure from Philip K. Dick award-winner, Rudy Rucker, reads like a ripped-from-Reddit romp of white hat hacking, artificial intelligence. run amok, and an unstoppable electronic 'bugs.'From a two-time winner of the Philip K. Dick award, and one of the founding fathers of cyberpunk comes a novel about a very modern nightmare: the most destructive computer virus ever has been traced to your machine. Computer programmer Jerzy Rugby spends his days blissfully hacking away in cyberspace - aiding the GoMotion Corporation in its noble quest to create intelligent robots. Then an electronic ant gets into the machinery ... then more ants .... then millions and millions of the nasty viral pests appear out of nowhere to wreak havoc throughout the Net. And suddenly Jerzy Rugby is Public Enemy Number One, wanted for sabotage, computer crime, and treason - a patsy who must now get to the bottom of the virtual insectile plague. Rudy Rucker warms the cockles of my heart ... I think of him as the Scarlet Pimpernel of science fiction. - Philip Jose Farmer |
| computer science foundation course: Computer Science and Educational Informatization Jianhou Gan, Yi Pan, Juxiang Zhou, Dong Liu, Xianhua Song, Zeguang Lu, 2024-02-10 These two volumes constitute the revised selected papers of the 5th International Conference, CSEI 2023, held in Kunming, China, during August 11–13, 2023. The 76 full papers and the 21 short papers included in this volume were carefully reviewed and selected from 297 submissions. They focus on computer science, education informatization and engineering education, innovative application for the deeper integration of education practice and information technology, educational informatization and big data for education. |
| computer science foundation course: Program Report - National Science Foundation National Science Foundation (U.S.), 1977 |
| computer science foundation course: Introduction to Programming Using Java David Eck, 2009-09 This is a free, on-line textbook on introductory programming using Java. This book is directed mainly towards beginning programmers, although it might also be useful for experienced programmers who want to learn more about Java. It is an introductory text and does not provide complete coverage of the Java language. The text is a PDF and is suitable for printing or on-screen reading. It contains internal links for navigation and external links to source code files, exercise solutions, and other resources. Contents: 1) Overview: The Mental Landscape. 2) Programming in the Small I: Names and Things. 3) Programming in the Small II: Control. 4) Programming in the Large I: Subroutines. 5) Programming in the Large II: Objects and Classes. 6) Introduction to GUI Programming. 7) Arrays. 8) Correctness and Robustness. 9) Linked Data Structures and Recursion. 10) Generic Programming and Collection Classes. 11) Files and Networking. 12) Advanced GUI Programming. Appendices: Source Code for All Examples in this Book, and News and Errata. |
| computer science foundation course: Calculus Revisited R.W. Carroll, 2002-12-31 In this book the details of many calculations are provided for access to work in quantum groups, algebraic differential calculus, noncommutative geometry, fuzzy physics, discrete geometry, gauge theory, quantum integrable systems, braiding, finite topological spaces, some aspects of geometry and quantum mechanics and gravity. |
| computer science foundation course: Study Skills 1 Saddleback Educational Publishing Staff, Laurel Associates Inc Staff, 2008-09-01 From reducing the stress of test taking to looking up words in a dictionary, these binders have it all. Includes organizing for study, improving memory, taking notes, goal setting, and more. Topics Include: Time Management, Planning and Goal Setting, Developing a Learning Style, Paraphrasing and Summarizing, Answering Essay Questions, and more... |
| computer science foundation course: National Science Foundation Directory of NSF-supported Teacher Enhancement Projects , 1985 |
Primary Career Cluster: CTE.Standards@tn - TN.gov
Computer Science Foundations (CSF) is a course intended to provide students with exposure to various information technology occupations and pathways such as Networking Systems, …
Information Technology Program Guide 2024-2025
Computer Science Program (Must teach three courses from this program list within two years.) This pathway includes the study of theoretical algorithms and the practical problems involved in …
Computer Science 2023-2024
*Computer Science majors will be assigned a faculty advisor when they pass the foundation exam. Revised 2/20/2023 Computer Recommendations for incoming students in 2023-2024
Computing Foundations for a Digital Age
Create a definition of computer science and computational thinking and explore growing and emerging careers in the computer science and information technology fields, as well as how …
CS 182: Foundations of Computer Science Syllabus - Purdue …
McGraw-Hill Science/Engineering/Math; latest edition. Approximate Course Outline (See the course web page for a detailed, lecture-by-lecture, course outline.) • Basic Logic • The …
Foundations of Computer Science - University of Cambridge
I Foundations of Computer Science 1 This course has two objectives. First (and obvious) is to teach program-ming. Second is to present some fundamental principles of computer science, …
Course Syllabus - NYU Tandon School of Engineering
CS-GY6003-Foundations of Computer Science Course Information Instructor Students can contact the instructor anytime by email or directly through NYU classes, or by making an …
Programme Specification: Computer Science Foundation
The Computer Sciences and Engineering Foundation course will produce students ready for level 4 who; 1. are well informed on, and have a secure comprehension of, appropriate aspects of …
CS 1428: Foundations of Computer Science I Spring 2020
Course Description: Introductory course for computer science majors, minors and others desiring a technical introduction to computer science. The course emphasizes problem solving, …
Computer Science Course Flowchart - University of Central …
Computer Science 1. General Information This pamphlet briefly outlines the undergraduate Computer Science (CS) program for the Bachelor of Science degree offered by the Department …
C Complete 2 courses Foundation Exam - University of Central …
*Computer Science majors will be assigned a faculty advisor when they pass the foundation exam. Revised 3/15/2022 Computer Recommendations for incoming students in 2022-2023
Course Structure and Syllabus for Career Related First Degree …
The First Degree Programme in Computer Science is designed with the objective of equipping the students to cope with the emerging trends and challenges in field of computers and interrelated …
Course Specification - .NET Framework
You will study the fundamental concepts of computer science, including computer programming, data structures and algorithms, information systems, computer networks and computer …
Computer Science Foundations - TN.gov
Computer Science Foundations (CSF) is a course intended to provide students with exposure to various information technology occupations and pathways such as Networking Systems, …
Course Selection Guide Computer Science Program
This document is an unofficial course selection guide for the Computer Science program. The course selection guide is meant to serve as a roadmap, giving you a destination and a generic …
MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE - BIET
This course will discuss fundamental concepts and tools in discrete mathematics with emphasis on their applications to computer science. Topics include logic and Boolean circuits, sets, …
Foundations of Computer Science - University of Cambridge
I Foundations of Computer Science 1 This course has two aims. The first is to teach programming. The second is to present some fundamental principles of computer science, …
Course Specification - .NET Framework
You will study the fundamental concepts of computer science, including computer programming, data structures and algorithms, information systems, computer networks and computer …
BSc(Hons) Computer Science (with Foundation Year)
BSc(Hons) Computer Science shows you how to analyse complex problems, design the algorithms to solve them, and write the programs that put these solutions into practice. There's …
Foundations of Computer Science - University of Cambridge
I Foundations of Computer Science 1 This course has two aims. The first is to teach programming. The second is to present some fundamental principles of computer science, …
Primary Career Cluster: CTE.Standards@tn - TN.gov
Computer Science Foundations (CSF) is a course intended to provide students with exposure to various information technology occupations and pathways such as Networking Systems, Coding, …
Information Technology Program Guide 2024-2025
Computer Science Program (Must teach three courses from this program list within two years.) This pathway includes the study of theoretical algorithms and the practical problems involved in …
Computer Science 2023-2024
*Computer Science majors will be assigned a faculty advisor when they pass the foundation exam. Revised 2/20/2023 Computer Recommendations for incoming students in 2023-2024
Computing Foundations for a Digital Age
Create a definition of computer science and computational thinking and explore growing and emerging careers in the computer science and information technology fields, as well as how …
CS 182: Foundations of Computer Science Syllabus - Purdue …
McGraw-Hill Science/Engineering/Math; latest edition. Approximate Course Outline (See the course web page for a detailed, lecture-by-lecture, course outline.) • Basic Logic • The Language of …
Foundations of Computer Science - University of Cambridge
I Foundations of Computer Science 1 This course has two objectives. First (and obvious) is to teach program-ming. Second is to present some fundamental principles of computer science, …
Course Syllabus - NYU Tandon School of Engineering
CS-GY6003-Foundations of Computer Science Course Information Instructor Students can contact the instructor anytime by email or directly through NYU classes, or by making an appointment …
Programme Specification: Computer Science Foundation
The Computer Sciences and Engineering Foundation course will produce students ready for level 4 who; 1. are well informed on, and have a secure comprehension of, appropriate aspects of …
CS 1428: Foundations of Computer Science I Spring 2020
Course Description: Introductory course for computer science majors, minors and others desiring a technical introduction to computer science. The course emphasizes problem solving, algorithm …
Computer Science Course Flowchart - University of Central …
Computer Science 1. General Information This pamphlet briefly outlines the undergraduate Computer Science (CS) program for the Bachelor of Science degree offered by the Department …
C Complete 2 courses Foundation Exam - University of …
*Computer Science majors will be assigned a faculty advisor when they pass the foundation exam. Revised 3/15/2022 Computer Recommendations for incoming students in 2022-2023
Course Structure and Syllabus for Career Related First Degree …
The First Degree Programme in Computer Science is designed with the objective of equipping the students to cope with the emerging trends and challenges in field of computers and interrelated …
Course Specification - .NET Framework
You will study the fundamental concepts of computer science, including computer programming, data structures and algorithms, information systems, computer networks and computer …
Computer Science Foundations - TN.gov
Computer Science Foundations (CSF) is a course intended to provide students with exposure to various information technology occupations and pathways such as Networking Systems, Coding, …
Course Selection Guide Computer Science Program
This document is an unofficial course selection guide for the Computer Science program. The course selection guide is meant to serve as a roadmap, giving you a destination and a generic …
MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE
This course will discuss fundamental concepts and tools in discrete mathematics with emphasis on their applications to computer science. Topics include logic and Boolean circuits, sets, functions, …
Foundations of Computer Science - University of Cambridge
I Foundations of Computer Science 1 This course has two aims. The first is to teach programming. The second is to present some fundamental principles of computer science, especially algorithm …
Course Specification - .NET Framework
You will study the fundamental concepts of computer science, including computer programming, data structures and algorithms, information systems, computer networks and computer …
BSc(Hons) Computer Science (with Foundation Year)
BSc(Hons) Computer Science shows you how to analyse complex problems, design the algorithms to solve them, and write the programs that put these solutions into practice. There's a strong AI …
Foundations of Computer Science - University of Cambridge
I Foundations of Computer Science 1 This course has two aims. The first is to teach programming. The second is to present some fundamental principles of computer science, especially algorithm …
