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| computer science course pdf: Cambridge IGCSE Computer Science David Watson, Helen Williams, 2015-01-30 Endorsed by Cambridge Assessment International Education. Develop computational thinking and programming skills with complete coverage of the latest syllabus from experienced examiners and teachers. - Follows the order of the syllabus exactly, ensuring complete coverage - Introduces students to self-learning exercises, helping them learn how to use their knowledge in new scenarios - Accompanying animation files of the key concepts are available to download for free online. www.hoddereducation.co.uk/cambridgeextras-1 - Answers are available on the Teacher's CD. This book covers the IGCSE (0478), O Level (2210) and US IGCSE entry (0473) syllabuses, which are for first examination 2015. It may also be a useful reference for students taking the new Computer Science AS level course (9608). |
| computer science course pdf: Introduction to Computing David Evans, 2011-12-07 Introduction to Computing is a comprehensive text designed for the CS0 (Intro to CS) course at the college level. It may also be used as a primary text for the Advanced Placement Computer Science course at the high school level. |
| computer science course pdf: Computer Science Robert Sedgewick, Kevin Wayne, 2016-06-17 Named a Notable Book in the 21st Annual Best of Computing list by the ACM! Robert Sedgewick and Kevin Wayne’s Computer Science: An Interdisciplinary Approach is the ideal modern introduction to computer science with Java programming for both students and professionals. Taking a broad, applications-based approach, Sedgewick and Wayne teach through important examples from science, mathematics, engineering, finance, and commercial computing. The book demystifies computation, explains its intellectual underpinnings, and covers the essential elements of programming and computational problem solving in today’s environments. The authors begin by introducing basic programming elements such as variables, conditionals, loops, arrays, and I/O. Next, they turn to functions, introducing key modular programming concepts, including components and reuse. They present a modern introduction to object-oriented programming, covering current programming paradigms and approaches to data abstraction. Building on this foundation, Sedgewick and Wayne widen their focus to the broader discipline of computer science. They introduce classical sorting and searching algorithms, fundamental data structures and their application, and scientific techniques for assessing an implementation’s performance. Using abstract models, readers learn to answer basic questions about computation, gaining insight for practical application. Finally, the authors show how machine architecture links the theory of computing to real computers, and to the field’s history and evolution. For each concept, the authors present all the information readers need to build confidence, together with examples that solve intriguing problems. Each chapter contains question-and-answer sections, self-study drills, and challenging problems that demand creative solutions. Companion web site (introcs.cs.princeton.edu/java) contains Extensive supplementary information, including suggested approaches to programming assignments, checklists, and FAQs Graphics and sound libraries Links to program code and test data Solutions to selected exercises Chapter summaries Detailed instructions for installing a Java programming environment Detailed problem sets and projects Companion 20-part series of video lectures is available at informit.com/title/9780134493831 |
| computer science course pdf: Introduction to Computation and Programming Using Python, second edition John V. Guttag, 2016-08-12 The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics. |
| computer science course pdf: Discrete Mathematics for Computer Science Gary Haggard, John Schlipf, Sue Whitesides, 2006 Master the fundamentals of discrete mathematics with DISCRETE MATHEMATICS FOR COMPUTER SCIENCE with Student Solutions Manual CD-ROM! An increasing number of computer scientists from diverse areas are using discrete mathematical structures to explain concepts and problems and this mathematics text shows you how to express precise ideas in clear mathematical language. Through a wealth of exercises and examples, you will learn how mastering discrete mathematics will help you develop important reasoning skills that will continue to be useful throughout your career. |
| computer science course pdf: Foundations of Computer Science Alfred V. Aho, Jeffrey D. Ullman, 1994-10-15 |
| computer science course pdf: Guide to Teaching Computer Science Orit Hazzan, Tami Lapidot, Noa Ragonis, 2015-01-07 This textbook presents both a conceptual framework and detailed implementation guidelines for computer science (CS) teaching. Updated with the latest teaching approaches and trends, and expanded with new learning activities, the content of this new edition is clearly written and structured to be applicable to all levels of CS education and for any teaching organization. Features: provides 110 detailed learning activities; reviews curriculum and cross-curriculum topics in CS; explores the benefits of CS education research; describes strategies for cultivating problem-solving skills, for assessing learning processes, and for dealing with pupils’ misunderstandings; proposes active-learning-based classroom teaching methods, including lab-based teaching; discusses various types of questions that a CS instructor or trainer can use for a range of teaching situations; investigates thoroughly issues of lesson planning and course design; examines the first field teaching experiences gained by CS teachers. |
| computer science course pdf: 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 course pdf: What Is Computer Science? Daniel Page, Nigel Smart, 2013-12-31 This engaging and accessible text addresses the fundamental question: What Is Computer Science? The book showcases a set of representative concepts broadly connected by the theme of information security, for which the presentation of each topic can be treated as a mini lecture course, demonstrating how it allows us to solve real problems, as well as how it relates to other subjects. The discussions are further supported by numerous examples and practical hands-on exercises. Features: presents a concise introduction to the study of algorithms and describes how computers work; introduces the concepts of data compression, and error detection and correction; highlights the role of data structures; explores the topic of web-search; reviews both historic and modern cryptographic schemes, examines how a physical system can leak information and discusses the idea of randomness; investigates the science of steganography; provides additional supplementary material at an associated website. |
| computer science course pdf: Computational Complexity Sanjeev Arora, Boaz Barak, 2009-04-20 New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students. |
| computer science course pdf: Writing for Computer Science Justin Zobel, 2004-06-03 A complete update to a classic, respected resource Invaluable reference, supplying a comprehensive overview on how to undertake and present research |
| computer science course pdf: Cambridge International AS and A Level Computer Science Coursebook Sylvia Langfield, Dave Duddell, 2015-12-17 Cambridge International AS and A Level Computer Science Coursebook delivers an accessible guide to theoretical and practical skills in Computer Science, with a clear progression of tasks that help to consolidate and develop knowledge. Cambridge International AS and A Level Computer Science Coursebook offers students detailed descriptions of the concepts, reinforced with examples that outline complex subject matter in a clear way. Alongside fundamental definitions, higher level programming skills are developed through the explanation of processes and consolidated by practical exam-type questions for students to attempt.-- Publisher description. |
| computer science course pdf: How to Design Programs, second edition Matthias Felleisen, Robert Bruce Findler, Matthew Flatt, Shriram Krishnamurthi, 2018-05-25 A completely revised edition, offering new design recipes for interactive programs and support for images as plain values, testing, event-driven programming, and even distributed programming. This introduction to programming places computer science at the core of a liberal arts education. Unlike other introductory books, it focuses on the program design process, presenting program design guidelines that show the reader how to analyze a problem statement, how to formulate concise goals, how to make up examples, how to develop an outline of the solution, how to finish the program, and how to test it. Because learning to design programs is about the study of principles and the acquisition of transferable skills, the text does not use an off-the-shelf industrial language but presents a tailor-made teaching language. For the same reason, it offers DrRacket, a programming environment for novices that supports playful, feedback-oriented learning. The environment grows with readers as they master the material in the book until it supports a full-fledged language for the whole spectrum of programming tasks. This second edition has been completely revised. While the book continues to teach a systematic approach to program design, the second edition introduces different design recipes for interactive programs with graphical interfaces and batch programs. It also enriches its design recipes for functions with numerous new hints. Finally, the teaching languages and their IDE now come with support for images as plain values, testing, event-driven programming, and even distributed programming. |
| computer science course pdf: 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 course pdf: The Science of Programming David Gries, 2012-12-06 Describes basic programming principles and their step-by- step applications.Numerous examples are included. |
| computer science course pdf: The Usefulness of Useless Knowledge Abraham Flexner, Robbert Dijkgraaf, 2017-02-21 A short, provocative book about why useless science often leads to humanity's greatest technological breakthroughs A forty-year tightening of funding for scientific research has meant that resources are increasingly directed toward applied or practical outcomes, with the intent of creating products of immediate value. In such a scenario, it makes sense to focus on the most identifiable and urgent problems, right? Actually, it doesn't. In his classic essay The Usefulness of Useless Knowledge, Abraham Flexner, the founding director of the Institute for Advanced Study in Princeton and the man who helped bring Albert Einstein to the United States, describes a great paradox of scientific research. The search for answers to deep questions, motivated solely by curiosity and without concern for applications, often leads not only to the greatest scientific discoveries but also to the most revolutionary technological breakthroughs. In short, no quantum mechanics, no computer chips. This brief book includes Flexner's timeless 1939 essay alongside a new companion essay by Robbert Dijkgraaf, the Institute's current director, in which he shows that Flexner's defense of the value of the unobstructed pursuit of useless knowledge may be even more relevant today than it was in the early twentieth century. Dijkgraaf describes how basic research has led to major transformations in the past century and explains why it is an essential precondition of innovation and the first step in social and cultural change. He makes the case that society can achieve deeper understanding and practical progress today and tomorrow only by truly valuing and substantially funding the curiosity-driven pursuit of useless knowledge in both the sciences and the humanities. |
| computer science course pdf: 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 course pdf: 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 course pdf: Logic for Computer Scientists Uwe Schöning, 2009-11-03 This book introduces the notions and methods of formal logic from a computer science standpoint, covering propositional logic, predicate logic, and foundations of logic programming. The classic text is replete with illustrative examples and exercises. It presents applications and themes of computer science research such as resolution, automated deduction, and logic programming in a rigorous but readable way. The style and scope of the work, rounded out by the inclusion of exercises, make this an excellent textbook for an advanced undergraduate course in logic for computer scientists. |
| computer science course pdf: Introduction to Computer Science: Coding Kathleen M. Austin, Lorraine N. Bergkvist, 2017-08-16 Learn the basics of computer science through coding with Scratch, App Inventor, Alice, and HTML. |
| computer science course pdf: Mastering Algorithms with C Kyle Loudon, 1999 Implementations, as well as interesting, real-world examples of each data structure and algorithm, are shown in the text. Full source code appears on the accompanying disk. |
| computer science course pdf: Cambridge IGCSE and O Level Computer Science Second Edition David Watson, Helen Williams, 2021-04-16 This title is endorsed by Cambridge Assessment International Education to support the full syllabus for examination from 2023. Benefit from the knowledge of our renowned expert authors to navigate through the content of the updated Cambridge IGCSETM and O Level Computer Science syllabuses (0478/0984/2210). - Develop computational thinking and problem-solving skills: clearly-explained concepts are followed by opportunities to implement in the programming language of choice. - Build an understanding of computer systems and associated technologies: carefully prepared worked examples explain new ideas alongside activities to test and consolidate. - Navigate the syllabus confidently: supplementary subject content is flagged clearly, with introductions to each topic outlining the learning objectives. - Satisfy curiosity: students are encouraged to deepen their knowledge and understanding of the subject with Extension Activities and Find Out More. - Consolidate skills and check understanding: self-assessment questions, activities and exam-style questions are embedded throughout the book, alongside key definitions of technical terms and a glossary. Answers to the Student Book are available in Cambridge IGCSE and O Level Computer Science Teacher's Guide with Boost Subscription 9781398318502 |
| computer science course pdf: Introduction to Scientific Computing and Data Analysis Mark H. Holmes, 2023-07-11 This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra. |
| computer science course pdf: HT THINK LIKE A COMPUTER SCIEN Jeffrey Elkner, Allen B. Downey, Chris Meyers, 2016-10-04 The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That's why this chapter is called, The way of the program. On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer. |
| computer science course pdf: Edexcel GCSE Computer Science Student Book Ann Weidmann, David Waller, Alex Hadwen-Bennett, Chris Charles, Shaun Whorton, Jason Welch, 2016-05-31 Supporting great computer science teaching through a scenario-based approach to problem solving and computational thinking. Our resources are designed to inspire and motivate students by relating and applying their skills to real-world contexts and making learning relevant. |
| computer science course pdf: Web Technologies: A Computer Science Perspective (Subscription) Jeffrey C. Jackson, 2011-11-21 This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Web Technologies: A Computer Science Perspective is ideal for courses in Web-based Systems (aka Web/Internet Programming/Systems) in Computer Science, MIS, and IT departments. This text introduces the key technologies that have been developed as part of the birth and maturation of the World Wide Web. It provides a consistent, in-depth treatment of technologies that are unlikely to receive detailed coverage in non-Web computer science courses. Students will find an ongoing case study that integrates a wide spectrum of Web technologies, guidance on setting up their own software environments, and a variety of exercises and project assignments. |
| computer science course pdf: Dirk Gently's Holistic Detective Agency Douglas Adams, 2014-10-07 Now a BBC America TV series event--Cover. |
| computer science course pdf: 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 course pdf: Computer Science J. Glenn Brookshear, 2012 Computer Science: An Overview uses broad coverage and clear exposition to present a complete picture of the dynamic computer science field. Accessible to students from all backgrounds, Glenn Brookshear uses a language-independent context to encourage the development of a practical, realistic understanding of the field. An overview of each of the important areas of Computer Science (e.g. Networking, OS, Computer Architecture, Algorithms) provides students with a general level of proficiency for future courses. The Eleventh Edition features two new contributing authors (David Smith -- Indiana University of PA; Dennis Brylow -- Marquette University), new, modern examples, and updated coverage based on current technology. |
| computer science course pdf: Ultimate Go Notebook William Kennedy, 2021-07-08 |
| computer science course pdf: Introduction to Computer Science ITL Education Solutions Limited, 2011 Discusses most ideas behind a computer in a simple and straightforward manner. The book is also useful to computer enthusiasts who wish to gain fundamental knowledge of computers. |
| computer science course pdf: Introduction to the Theory of Computation Michael Sipser, 2006 Intended as an upper-level undergraduate or introductory graduate text in computer science theory, this book lucidly covers the key concepts and theorems of the theory of computation. The presentation is remarkably clear; for example, the proof idea, which offers the reader an intuitive feel for how the proof was constructed, accompanies many of the theorems and a proof. Introduction to the Theory of Computation covers the usual topics for this type of text plus it features a solid section on complexity theory--including an entire chapter on space complexity. The final chapter introduces more advanced topics, such as the discussion of complexity classes associated with probabilistic algorithms. |
| computer science course pdf: Essential Questions Jay McTighe, Grant Wiggins, 2013-03-27 What are essential questions, and how do they differ from other kinds of questions? What's so great about them? Why should you design and use essential questions in your classroom? Essential questions (EQs) help target standards as you organize curriculum content into coherent units that yield focused and thoughtful learning. In the classroom, EQs are used to stimulate students' discussions and promote a deeper understanding of the content. Whether you are an Understanding by Design (UbD) devotee or are searching for ways to address standards—local or Common Core State Standards—in an engaging way, Jay McTighe and Grant Wiggins provide practical guidance on how to design, initiate, and embed inquiry-based teaching and learning in your classroom. Offering dozens of examples, the authors explore the usefulness of EQs in all K-12 content areas, including skill-based areas such as math, PE, language instruction, and arts education. As an important element of their backward design approach to designing curriculum, instruction, and assessment, the authors *Give a comprehensive explanation of why EQs are so important; *Explore seven defining characteristics of EQs; *Distinguish between topical and overarching questions and their uses; *Outline the rationale for using EQs as the focal point in creating units of study; and *Show how to create effective EQs, working from sources including standards, desired understandings, and student misconceptions. Using essential questions can be challenging—for both teachers and students—and this book provides guidance through practical and proven processes, as well as suggested response strategies to encourage student engagement. Finally, you will learn how to create a culture of inquiry so that all members of the educational community—students, teachers, and administrators—benefit from the increased rigor and deepened understanding that emerge when essential questions become a guiding force for learners of all ages. |
| computer science course pdf: Categories and Computer Science R. F. C. Walters, Richard F. Walters, 1991 Category theory has become increasingly important and popular in computer science, and many universities now have introductions to category theory as part of their courses for undergraduate computer scientists. The author is a respected category theorist and has based this textbook on a course given over the last few years at the University of Sydney. The theory is developed in a straightforward way, and is enriched with many examples from computer science. Thus this book meets the needs of undergradute computer scientists, and yet retains a level of mathematical correctness that will broaden its appeal to include students of mathematics new to category theory. |
| computer science course pdf: Connecting Discrete Mathematics and Computer Science David Liben-Nowell, 2022-08-04 Computer science majors taking a non-programming-based course like discrete mathematics might ask 'Why do I need to learn this?' Written with these students in mind, this text introduces the mathematical foundations of computer science by providing a comprehensive treatment of standard technical topics while simultaneously illustrating some of the broad-ranging applications of that material throughout the field. Chapters on core topics from discrete structures – like logic, proofs, number theory, counting, probability, graphs – are augmented with around 60 'computer science connections' pages introducing their applications: for example, game trees (logic), triangulation of scenes in computer graphics (induction), the Enigma machine (counting), algorithmic bias (relations), differential privacy (probability), and paired kidney transplants (graphs). Pedagogical features include 'Why You Might Care' sections, quick-reference chapter guides and key terms and results summaries, problem-solving and writing tips, 'Taking it Further' asides with more technical details, and around 1700 exercises, 435 worked examples, and 480 figures. |
| computer science course pdf: Princeton Review AP Computer Science A Prep, 2022 The Princeton Review, 2021-08-31 Make sure you’re studying with the most up-to-date prep materials! Look for the newest edition of this title, The Princeton Review AP Computer Science A Prep, 2023 (ISBN: 9780593450727, on-sale September 2020). Publisher's Note: Products purchased from third-party sellers are not guaranteed by the publisher for quality or authenticity, and may not include access to online tests or materials included with the original product. |
| computer science course pdf: Algorithms Unplugged Berthold Vöcking, Helmut Alt, Martin Dietzfelbinger, Rüdiger Reischuk, Christian Scheideler, Heribert Vollmer, Dorothea Wagner, 2010-12-10 Algorithms specify the way computers process information and how they execute tasks. Many recent technological innovations and achievements rely on algorithmic ideas – they facilitate new applications in science, medicine, production, logistics, traffic, communi¬cation and entertainment. Efficient algorithms not only enable your personal computer to execute the newest generation of games with features unimaginable only a few years ago, they are also key to several recent scientific breakthroughs – for example, the sequencing of the human genome would not have been possible without the invention of new algorithmic ideas that speed up computations by several orders of magnitude. The greatest improvements in the area of algorithms rely on beautiful ideas for tackling computational tasks more efficiently. The problems solved are not restricted to arithmetic tasks in a narrow sense but often relate to exciting questions of nonmathematical flavor, such as: How can I find the exit out of a maze? How can I partition a treasure map so that the treasure can only be found if all parts of the map are recombined? How should I plan my trip to minimize cost? Solving these challenging problems requires logical reasoning, geometric and combinatorial imagination, and, last but not least, creativity – the skills needed for the design and analysis of algorithms. In this book we present some of the most beautiful algorithmic ideas in 41 articles written in colloquial, nontechnical language. Most of the articles arose out of an initiative among German-language universities to communicate the fascination of algorithms and computer science to high-school students. The book can be understood without any prior knowledge of algorithms and computing, and it will be an enlightening and fun read for students and interested adults. |
| computer science course pdf: Introduction to Programming in Java: An Interdisciplinary Approach Robert Sedgewick, Kevin Wayne, 2013-07-31 By emphasizing the application of computer programming not only in success stories in the software industry but also in familiar scenarios in physical and biological science, engineering, and applied mathematics, Introduction to Programming in Java takes an interdisciplinary approach to teaching programming with the Java(TM) programming language. Interesting applications in these fields foster a foundation of computer science concepts and programming skills that students can use in later courses while demonstrating that computation is an integral part of the modern world. Ten years in development, this book thoroughly covers the field and is ideal for traditional introductory programming courses. It can also be used as a supplement or a main text for courses that integrate programming with mathematics, science, or engineering. |
| computer science course pdf: 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 course pdf: Models of Computation , 2002-01-01 |
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Computer Science Curriculum 2008 [5]: This was presented as an interim revision of Computing Curricula 2001. Computer Science Curricula 2013 [6]: This was the most recent version of the …
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course closer to the diamond may be taken at the same time as the co-requisite. The co-requisite is a prerequisite for any course that requires the course closer to the diamond. A line indicates …
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Guide to the MSCS Program Sheet - Computer Science
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Department of Electrical Engineering and Computer Science
Computer Science and the Department of Economics (Course 14), this program is for students who wish to specialize in computer science, economics, and data science.
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Computer Science and the Department of Economics (Course 14), this program is for students who wish to specialize in computer science, economics, and data science.
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Computer Science Curriculum (2024-2025 Catalog Year) 120 …
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CSE—Computer Science and Engineering 1 COMPUTER SCIENCE AND ENGINEERING CSE Department of Computer Science and Engineering College of Engineering 100 Computer …
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Computer Science — Begin with CSCI 103 Computer Science — Begin with CSCI 102 The Computer Science (CSCI) program prepares students to work in the areas of software design, …
