| computer science 101 by stanford university: Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Policy and Global Affairs, Board on Higher Education and Workforce, Committee on the Growth of Computer Science Undergraduate Enrollments, 2018-04-28 The field of computer science (CS) is currently experiencing a surge in undergraduate degree production and course enrollments, which is straining program resources at many institutions and causing concern among faculty and administrators about how best to respond to the rapidly growing demand. There is also significant interest about what this growth will mean for the future of CS programs, the role of computer science in academic institutions, the field as a whole, and U.S. society more broadly. Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends. It examines drivers of the current enrollment surge, relationships between the surge and current and potential gains in diversity in the field, and the potential impacts of responses to the increased demand for computing in higher education, and it considers the likely effects of those responses on students, faculty, and institutions. This report provides recommendations for what institutions of higher education, government agencies, and the private sector can do to respond to the surge and plan for a strong and sustainable future for the field of CS in general, the health of the institutions of higher education, and the prosperity of the nation. |
| computer science 101 by stanford university: Programming Methodology Annabelle Mclver, Carroll Morgan, 2002-10-01 Written by the members of the IFIP Working Group 2.3 (Programming Methodology) this text constitutes an exciting reference on the front-line of research activity in programming methodology. The range of subjects reflects the current interests of the members, and will offer insightful and controversial opinions on modern programming methods and practice. The material is arranged in thematic sections, each one introduced by a problem which epitomizes the spirit of that topic. The exemplary problem will encourage vigorous discussion and will form the basis for an introduction/tutorial for its section. |
| computer science 101 by stanford university: Science and Cooking: Physics Meets Food, From Homemade to Haute Cuisine Michael Brenner, Pia Sörensen, David Weitz, 2020-10-20 Based on the popular Harvard University and edX course, Science and Cooking explores the scientific basis of why recipes work. The spectacular culinary creations of modern cuisine are the stuff of countless articles and social media feeds. But to a scientist they are also perfect pedagogical explorations into the basic scientific principles of cooking. In Science and Cooking, Harvard professors Michael Brenner, Pia Sörensen, and David Weitz bring the classroom to your kitchen to teach the physics and chemistry underlying every recipe. Why do we knead bread? What determines the temperature at which we cook a steak, or the amount of time our chocolate chip cookies spend in the oven? Science and Cooking answers these questions and more through hands-on experiments and recipes from renowned chefs such as Christina Tosi, Joanne Chang, and Wylie Dufresne, all beautifully illustrated in full color. With engaging introductions from revolutionary chefs and collaborators Ferran Adria and José Andrés, Science and Cooking will change the way you approach both subjects—in your kitchen and beyond. |
| computer science 101 by stanford university: 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 101 by stanford university: Introduction to Information Retrieval Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze, 2008-07-07 Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures. |
| computer science 101 by stanford university: Principles of Computer System Design Jerome H. Saltzer, M. Frans Kaashoek, 2009-05-21 Principles of Computer System Design is the first textbook to take a principles-based approach to the computer system design. It identifies, examines, and illustrates fundamental concepts in computer system design that are common across operating systems, networks, database systems, distributed systems, programming languages, software engineering, security, fault tolerance, and architecture.Through carefully analyzed case studies from each of these disciplines, it demonstrates how to apply these concepts to tackle practical system design problems. To support the focus on design, the text identifies and explains abstractions that have proven successful in practice such as remote procedure call, client/service organization, file systems, data integrity, consistency, and authenticated messages. Most computer systems are built using a handful of such abstractions. The text describes how these abstractions are implemented, demonstrates how they are used in different systems, and prepares the reader to apply them in future designs.The book is recommended for junior and senior undergraduate students in Operating Systems, Distributed Systems, Distributed Operating Systems and/or Computer Systems Design courses; and professional computer systems designers. - Concepts of computer system design guided by fundamental principles - Cross-cutting approach that identifies abstractions common to networking, operating systems, transaction systems, distributed systems, architecture, and software engineering - Case studies that make the abstractions real: naming (DNS and the URL); file systems (the UNIX file system); clients and services (NFS); virtualization (virtual machines); scheduling (disk arms); security (TLS) - Numerous pseudocode fragments that provide concrete examples of abstract concepts - Extensive support. The authors and MIT OpenCourseWare provide on-line, free of charge, open educational resources, including additional chapters, course syllabi, board layouts and slides, lecture videos, and an archive of lecture schedules, class assignments, and design projects |
| computer science 101 by stanford university: Applied Cryptography Bruce Schneier, 2017-05-25 From the world's most renowned security technologist, Bruce Schneier, this 20th Anniversary Edition is the most definitive reference on cryptography ever published and is the seminal work on cryptography. Cryptographic techniques have applications far beyond the obvious uses of encoding and decoding information. For developers who need to know about capabilities, such as digital signatures, that depend on cryptographic techniques, there's no better overview than Applied Cryptography, the definitive book on the subject. Bruce Schneier covers general classes of cryptographic protocols and then specific techniques, detailing the inner workings of real-world cryptographic algorithms including the Data Encryption Standard and RSA public-key cryptosystems. The book includes source-code listings and extensive advice on the practical aspects of cryptography implementation, such as the importance of generating truly random numbers and of keeping keys secure. . . .the best introduction to cryptography I've ever seen. . . .The book the National Security Agency wanted never to be published. . . . -Wired Magazine . . .monumental . . . fascinating . . . comprehensive . . . the definitive work on cryptography for computer programmers . . . -Dr. Dobb's Journal . . .easily ranks as one of the most authoritative in its field. -PC Magazine The book details how programmers and electronic communications professionals can use cryptography-the technique of enciphering and deciphering messages-to maintain the privacy of computer data. It describes dozens of cryptography algorithms, gives practical advice on how to implement them into cryptographic software, and shows how they can be used to solve security problems. The book shows programmers who design computer applications, networks, and storage systems how they can build security into their software and systems. With a new Introduction by the author, this premium edition will be a keepsake for all those committed to computer and cyber security. |
| computer science 101 by stanford university: 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 101 by stanford university: Concepts in Programming Languages John C. Mitchell, 2003 A comprehensive undergraduate textbook covering both theory and practical design issues, with an emphasis on object-oriented languages. |
| computer science 101 by stanford university: Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers Stephen Boyd, Neal Parikh, Eric Chu, 2011 Surveys the theory and history of the alternating direction method of multipliers, and discusses its applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others. |
| computer science 101 by stanford university: Creating a Website: The Missing Manual Matthew MacDonald, 2015-06-18 You can easily create a professional-looking website with nothing more than an ordinary computer and some raw ambition. Want to build a blog, sell products, create forums, or promote an event? No problem! This friendly, jargon-free book gives you the techniques, tools, and advice you need to build a site and get it up on the Web. The important stuff you need to know: Master the basics. Learn HTML5, the language of the Web. Design good-looking pages. Use styles to build polished layouts. Get it online. Find a reliable web host and pick a good web address. Use time-saving tools. Learn free tools for creating web pages and tracking your visitors. Attract visitors. Make sure people can find your site through popular search engines like Google. Build a community. Encourage repeat visits with social media. Bring in the cash. Host Google ads, sell Amazon’s wares, or push your own products that people can buy via PayPal. Add pizzazz. Include audio, video, interactive menus, and a pinch of JavaScript. |
| computer science 101 by stanford university: 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 101 by stanford university: HTML5 Foundations Matt West, 2012-11-19 Master innovative and eye-catching website design with the exciting new Treehouse Series of books Turn plain words and images into stunning websites using HTML5 and this beautiful, full-colour guide. Taking you beyond the constraints of prebuilt themes and simple site building tools, this new Treehouse book combines practicality with inspiration to show you how to create fully customized, modern, and dazzling websites that make viewers want to stop and stay. The exciting new Treehouse Series of books is authored by Treehouse experts and packed with innovative design ideas and practical skill-building. If you're a web developer, web designer, hobbyist, or career-changer, every book in this practical new series should be on your bookshelf. Part of the new Treehouse Series of books, teaching you effective and compelling website development and design, helping you build practical skills Provides career-worthy information from Treehouse industry pros and trainers Explains HTML5 basics, such as how to format text, add scripts to pages, and use HTML5 for audio and video Also covers hypermedia, CSS and JavaScript, embedding video, geolocation, and much more Leverage pages of dazzling website design ideas and expert instruction with a new Treehouse Series book. |
| computer science 101 by stanford university: Computer Architecture John L. Hennessy, David A. Patterson, Krste Asanović, 2012 The computing world is in the middle of a revolution: mobile clients and cloud computing have emerged as the dominant paradigms driving programming and hardware innovation. This book focuses on the shift, exploring the ways in which software and technology in the 'cloud' are accessed by cell phones, tablets, laptops, and more |
| computer science 101 by stanford university: Learn to Code HTML and CSS Shay Howe, 2014-04-22 HTML and CSS can be a little daunting at first but fear not. This book, based on Shay Howe's popular workshop covers the basics and breaks down the barrier to entry, showing readers how they can start using HTML and CSS through practical techniques today. They'll find accompanying code examples online, while they explore topics such as the different structures of HTML and CSS, and common terms. After establishing a basic understanding of HTML and CSS a deeper dive is taken into the box model and how to work with floats. The book includes an exercise focused on cleaning up a web page by improving the user interface and design, solely using HTML and CSS. With a few quick changes the web page changes shape and comes to life. Interactive, technically up-to-the-minute and easy-to-understand, this book will advance a student's skills to a professional level. |
| computer science 101 by stanford university: Twenty Lectures on Algorithmic Game Theory Tim Roughgarden, 2016-08-30 Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management. |
| computer science 101 by stanford university: Foundations of Security Christoph Kern, Anita Kesavan, Neil Daswani, 2007-05-11 Software developers need to worry about security as never before. They need clear guidance on safe coding practices, and that’s exactly what this book delivers. The book does not delve deep into theory, or rant about the politics of security. Instead, it clearly and simply lays out the most common threats that programmers need to defend against. It then shows programmers how to make their defense. The book takes a broad focus, ranging over SQL injection, worms and buffer overflows, password security, and more. It sets programmers on the path towards successfully defending against the entire gamut of security threats that they might face. |
| computer science 101 by stanford university: Python Data Science Handbook Jake VanderPlas, 2016-11-21 For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms |
| computer science 101 by stanford university: Program Arcade Games Paul Craven, 2015-12-31 Learn and use Python and PyGame to design and build cool arcade games. In Program Arcade Games: With Python and PyGame, Second Edition, Dr. Paul Vincent Craven teaches you how to create fun and simple quiz games; integrate and start using graphics; animate graphics; integrate and use game controllers; add sound and bit-mapped graphics; and build grid-based games. After reading and using this book, you'll be able to learn to program and build simple arcade game applications using one of today's most popular programming languages, Python. You can even deploy onto Steam and other Linux-based game systems as well as Android, one of today's most popular mobile and tablet platforms. You'll learn: How to create quiz games How to integrate and start using graphics How to animate graphics How to integrate and use game controllers How to add sound and bit-mapped graphics How to build grid-based games Audience“div>This book assumes no prior programming knowledge. |
| computer science 101 by stanford university: Is-703.a Fema, 2010-01-15 Course Overview This course introduces resource management as described in the National Incident Management System (NIMS), and shows how systems for managing resources can be used to improve incident response. The course includes examples of best practices, lessons learned, and job aids to assist the participant in planning for resource management. The course includes the following lessons: -Lesson 1: Resource Management Overview -Lesson 2: Resource Management Planning -Lesson 3: Resource Typing & Readiness -Lesson 4: Resource Management During Incidents -Lesson 5: Resource Management & Complex Incidents -Lesson 6: Course Summary Note: IS-703.a is an updated version of the IS-703 course. The update version of the course includes expanded content about resource typing. If you have successfully completed IS-703, you may want to review the new version of the course, especially lesson 3. For credentialing purposes, the courses are equivalent. Course Objectives: At the conclusion of this course, you should be able to: -Establish systems for describing, inventorying, requesting, and tracking resources. -Activate these systems prior to and during an incident. -Dispatch resources prior to and during an incident. -Deactivate or recall resources during or after incidents. Primary Audience Federal, State, tribal, and local emergency managers; first responders to include incident commanders from all emergency management disciplines; private industry personnel responsible for coordination activities during a disaster; and voluntary agency personnel. Prerequisites N/A. However, completion of IS 700.a, National Incident Management System (NIMS), An Introduction, is recommended. |
| computer science 101 by stanford university: Computing the Future National Research Council, Computer Science and Telecommunications Board, Committee to Assess the Scope and Direction of Computer Science and Technology, 1992-02-01 Computers are increasingly the enabling devices of the information revolution, and computing is becoming ubiquitous in every corner of society, from manufacturing to telecommunications to pharmaceuticals to entertainment. Even more importantly, the face of computing is changing rapidly, as even traditional rivals such as IBM and Apple Computer begin to cooperate and new modes of computing are developed. Computing the Future presents a timely assessment of academic computer science and engineering (CS&E), examining what should be done to ensure continuing progress in making discoveries that will carry computing into the twenty-first century. Most importantly, it advocates a broader research and educational agenda that builds on the field's impressive accomplishments. The volume outlines a framework of priorities for CS&E, along with detailed recommendations for education, funding, and leadership. A core research agenda is outlined for these areas: processors and multiple-processor systems, data communications and networking, software engineering, information storage and retrieval, reliability, and user interfaces. This highly readable volume examines: Computer science and engineering as a discipline-how computer scientists and engineers are pushing back the frontiers of their field. How CS&E must change to meet the challenges of the future. The influence of strategic investment by federal agencies in CS&E research. Recent structural changes that affect the interaction of academic CS&E and the business environment. Specific examples of interdisciplinary and applications research in four areas: earth sciences and the environment, computational biology, commercial computing, and the long-term goal of a national electronic library. The volume provides a detailed look at undergraduate CS&E education, highlighting the limitations of four-year programs, and discusses the emerging importance of a master's degree in CS&E and the prospects for broadening the scope of the Ph.D. It also includes a brief look at continuing education. |
| computer science 101 by stanford university: Introduction to Applied Linear Algebra Stephen Boyd, Lieven Vandenberghe, 2018-06-07 A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples. |
| computer science 101 by stanford university: The Pedagogy of Pathologization Subini Ancy Annamma, 2017-11-15 WINNER OF THE 2019 AESA CRITICS' CHOICE BOOK AWARD WINNER OF THE 2018 NATIONAL WOMEN'S STUDIES ASSOCIATION ALISON PIEPMEIER BOOK PRIZE Linking powerful first-person narratives with structural analysis, The Pedagogy of Pathologization explores the construction of criminal identities in schools via the intersections of race, disability, and gender. amid the prevalence of targeted mass incarceration. Focusing uniquely on the pathologization of female students of color, whose voices are frequently engulfed by labels of deviance and disability, a distinct and underrepresented experience of the school-to-prison pipeline is detailed through original qualitative methods rooted in authentic narratives. The book’s DisCrit framework, grounded in interdisciplinary research, draws on scholarship from critical race theory, disability studies, education, women’s and girl’s studies, legal studies, and more. |
| computer science 101 by stanford university: Introduction to Mathematical Thinking Keith J. Devlin, 2012 Mathematical thinking is not the same as 'doing math'--unless you are a professional mathematician. For most people, 'doing math' means the application of procedures and symbolic manipulations. Mathematical thinking, in contrast, is what the name reflects, a way of thinking about things in the world that humans have developed over three thousand years. It does not have to be about mathematics at all, which means that many people can benefit from learning this powerful way of thinking, not just mathematicians and scientists.--Back cover. |
| computer science 101 by stanford university: Information Science 101 Anthony Debons, 2008 In the present generation, the attention paid to information continues to grow in importance. Much of this attention has been the result of an explosion in data-processing technology, with computers serving as the primary catalyst. However, other national events, such as hurricanes, floods, crime, and terror, are clearly tied to the importance of obtaining and processing information in our daily lives as well. For the last several decades, educational systems have responded to these technological advances by introducing, at an early age, the important role data-processing technology presents and will continue to represent. Many schools now include courses in computer science as part of their curriculum. Information Science 101 helps high school and college freshman identify and understand careers in information science. With this text, author Anthony Debons, one of the early founders of the discipline of Information Science, gives attention to the role of various disciplines in the field: library/documentation, tele-transmission, computer science and practice, decision making/problem solving, knowledge organization, and management. With examples, illustrations, chapter summaries, and exercises to help marry the human with the technological aspects of the field, this text gives a complete overview of Information Science, from its origins to the future of the field. |
| computer science 101 by stanford university: Speech & Language Processing Dan Jurafsky, 2000-09 |
| computer science 101 by stanford university: Reinforcement Learning, second edition Richard S. Sutton, Andrew G. Barto, 2018-11-13 The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning. |
| computer science 101 by stanford university: 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 101 by stanford university: Bitcoin and Cryptocurrency Technologies Arvind Narayanan, Joseph Bonneau, Edward Felten, Andrew Miller, Steven Goldfeder, 2016-07-19 An authoritative introduction to the exciting new technologies of digital money Bitcoin and Cryptocurrency Technologies provides a comprehensive introduction to the revolutionary yet often misunderstood new technologies of digital currency. Whether you are a student, software developer, tech entrepreneur, or researcher in computer science, this authoritative and self-contained book tells you everything you need to know about the new global money for the Internet age. How do Bitcoin and its block chain actually work? How secure are your bitcoins? How anonymous are their users? Can cryptocurrencies be regulated? These are some of the many questions this book answers. It begins by tracing the history and development of Bitcoin and cryptocurrencies, and then gives the conceptual and practical foundations you need to engineer secure software that interacts with the Bitcoin network as well as to integrate ideas from Bitcoin into your own projects. Topics include decentralization, mining, the politics of Bitcoin, altcoins and the cryptocurrency ecosystem, the future of Bitcoin, and more. An essential introduction to the new technologies of digital currency Covers the history and mechanics of Bitcoin and the block chain, security, decentralization, anonymity, politics and regulation, altcoins, and much more Features an accompanying website that includes instructional videos for each chapter, homework problems, programming assignments, and lecture slides Also suitable for use with the authors' Coursera online course Electronic solutions manual (available only to professors) |
| computer science 101 by stanford university: The Cambridge Handbook of Computing Education Research Sally A. Fincher, Anthony V. Robins, 2019-02-21 This Handbook describes the extent and shape of computing education research today. Over fifty leading researchers from academia and industry (including Google and Microsoft) have contributed chapters that together define and expand the evidence base. The foundational chapters set the field in context, articulate expertise from key disciplines, and form a practical guide for new researchers. They address what can be learned empirically, methodologically and theoretically from each area. The topic chapters explore issues that are of current interest, why they matter, and what is already known. They include discussion of motivational context, implications for practice, and open questions which might suggest future research. The authors provide an authoritative introduction to the field which is essential reading for policy makers, as well as both new and established researchers. |
| computer science 101 by stanford university: Art and Science of Java Eric Roberts, 2013-07-17 In The Art and Science of Java, Stanford professor and well-known leader in Computer Science Education Eric Roberts emphasizes the reader-friendly exposition that led to the success of The Art and Science of C. By following the recommendations of the Association of Computing Machinery's Java Task Force, this first edition text adopts a modern objects-first approach that introduces readers to useful hierarchies from the very beginning. Introduction; Programming by Example; Expressions; Statement Forms; Methods; Objects and Classes; Objects and Memory; Strings and Characters; Object-Oriented Graphics; Event-Driven Programs; Arrays and ArrayLists; Searching and Sorting; Collection Classes; Looking Ahead. A modern objects-first approach to the Java programming language that introduces readers to useful class hierarchies from the very beginning. |
| computer science 101 by stanford university: Algorithms Robert Sedgewick, Kevin Wayne, 2014-02-01 This book is Part I of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part I contains Chapters 1 through 3 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the Online Course link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience. |
| computer science 101 by stanford university: 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 101 by stanford university: Natural Language Processing with Python Steven Bird, Ewan Klein, Edward Loper, 2009-06-12 This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify named entities Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful. |
| computer science 101 by stanford university: Study and Research Guide in Computer Science Wolfgang Tölle, Jason Yasner, Michael Pieper, 2012-12-06 Computer science departments at universities in the U.S.A. are world renowned. This handy reference guide gives detailed profiles of 40 of the best known among them. The profiles are organized in a uniform layout to present basic information, faculty, curriculum, courses for graduate students, affiilated institutions, facilities, research areas, funding, selected projects, and collaborations. Two full alphabetical listings of professors are included, one giving their universities and the other their research areas. The guide will be indispensible for anyone - student or faculty, not only in the U.S.A. - interested in research and education in computer science in the U.S.A. |
| computer science 101 by stanford university: Computers at Risk National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Commission on Physical Sciences, Mathematics, and Applications, System Security Study Committee, 1990-02-01 Computers at Risk presents a comprehensive agenda for developing nationwide policies and practices for computer security. Specific recommendations are provided for industry and for government agencies engaged in computer security activities. The volume also outlines problems and opportunities in computer security research, recommends ways to improve the research infrastructure, and suggests topics for investigators. The book explores the diversity of the field, the need to engineer countermeasures based on speculation of what experts think computer attackers may do next, why the technology community has failed to respond to the need for enhanced security systems, how innovators could be encouraged to bring more options to the marketplace, and balancing the importance of security against the right of privacy. |
| computer science 101 by stanford university: Computation Structures Stephen A. Ward, Robert H. Halstead, 1990 Computer Systems Organization -- general. |
| computer science 101 by stanford university: Diagrammatic Representation and Reasoning Michael Anderson, Bernd Meyer, Patrick Olivier, 2011-06-27 The rise in computing and multimedia technology has spawned an increasing interest in the role of diagrams and sketches, not only for the purpose of conveying information but also for creative thinking and problem-solving. This book attempts to characterise the nature of a science of diagrams in a wide-ranging, multidisciplinary study that contains accounts of the most recent research results in computer science and psychology. Key topics include: cognitive aspects, formal aspects, and applications. It is a well-written and indispensable survey for researchers and students in the fields of cognitive science, artificial intelligence, human-computer interaction, and graphics and visualisation. |
| computer science 101 by stanford university: She’s In CTRL Anne-Marie Imafidon, 2022-09-08 'A practical and positive guide to using tech to change women's lives for the better' - Caroline Criado Perez, author of Invisible Women: exposing data bias in a world designed for men 'A powerful and inspiring call to action from one of Britain's brightest minds'- Yomi Adegoke, award-winning journalist, author of Slay in Your Lane etc. Why are women so under-represented in the tech world? Why does this matter? What can we do about it? A book that asks essential questions and provides long-overdue practical solutions. Perfect for readers of Invisible Women. Why do so many of us - particularly women - feel the tech world is beyond reach? Women are woefully under-represented in tech - they represent roughly a mere quarter of the UK STEM workforce. This means an ever-increasing series of big decisions are made by a small number of people, mainly men. So what are the challenges for all of us who want to wrest back control? How do we get past the gatekeepers? When we do, what are the opportunities that will open up - for us in our individual roles, and for the future of tech?. Dr Imafidon shows we have more agency than we think, drawing on her own experience and the stories of other pioneers and innovators to provide examples, exercises and practical guidance for how to get started and take control. There will always be problems. But, as we know, women are problem-solvers. |
| computer science 101 by stanford university: The IVY System , 1961 |
Computer Science 101 By Stanford University (book)
undergraduates and graduate students in computer science Based on feedback from extensive classroom experience the book has been carefully structured in order to make teaching more …
CS144 – Introduction to Computer Networking - Stanford …
What is a computer network? Why study computer networks? Nodes: Computers, dedicated routers, . . . Links: Coax, twisted pair, fibers, radio . . . ... But how do you build something like the …
Stanford Damjan Ostrelič STATEMENT OF …
computer science 101 please note: some online courses may draw on material from courses taught on-campus but they are not equivalent to on-campus courses. this statement does not affirm …
Stanford University | CS103: Math for Computer Science …
Stanford University | CS103: Math for Computer Science Handout PF Luca Trevisan 5/31/2014 Practice Final Problem 1 ... 101 = fjL(M) contains the string \101"g 1. is undecidable. Problem …
Computer Science 101 By Stanford University Copy
Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends It examines drivers of the …
Stanford WON SEOB SEO STATEMENT OF …
computer science 101 please note: some online courses may draw on material from courses taught on-campus but they are not equivalent to on-campus courses. this statement does not affirm …
STANFORD UNIVERSITY SCHOOL OF ENGINEERING
Transfer credits in Math, Science, Fundamentals, and TIS must Student Affairs in Terman 201. Transfer credits in Computer departmental representative. Courses may be listed under only one …
CS111, Lecture 1 - Stanford University
•Initially, computers were just one user a time, working directly at a computer. “OSes” were just I/O libraries shared by users for convenience and efficiency. •Over time, computers became more …
Suggested Reading 1. Introduction to Computers ... - Osmania …
Knowing computer: Basic Applications of Computer; Components of Computer System, Central Processing Unit (CPU), VDU, Keyboard and Mouse, Other input/output Devices, Computer …
CS144 – Introduction to Computer Networking - Stanford …
telephone, computer • What is a computer network? - A form of communication network—moves information - Nodes are general-purpose computers • Why study computer networks? - Many …
Cursos Gratuitos en Línea – Universidad de Stanford y Desafío …
Cursos Gratuitos en Línea – Universidad de Stanford y Desafío Latam Aprovecha la oportunidad de formarte con cursos gratuitos en áreas clave como ciencia de la computación, inteligencia …
Lecture 01: Welcome to CS110: P rinciples of Computer Systems
Not stocked at Stanford Bookstore b y design. You can buy a copy of it from Amazon if y ou want. "Computer Systems: A Programmer's Perspective", by Bryant and O'Hallaron "Principles of …
Essential C - Stanford University
This Stanford CS Education document tries to summarize all the basic features of the C language. The coverage is pretty quick, so it is most appropriate as review or for someone with some …
INTRODUCTION MACHINE LEARNING - Stanford University
Department of Computer Science Stanford University Stanford, CA 94305 e-mail: nilsson@cs.stanford.edu November 3, 1998 ... 7.6 Relationships Between ILP and Decision Tree …
The Handbook of Artificial Intelligence - Stanford University
These researchers and students, from Stanford and other AI centers, have contributed to Volumes I and II or are now engaged in preparing Volume 111 (being edited by Paul R. Cohen).
CS105: Introduction to Computer Science - Stanford University
Computer Science Dr. Patrick Young Winter 2010 Class Objectives The course objectives are as follows: to give students a strong background in the fundamentals of computer science, to …
RecipeNet: Image to Recipe/Nutritional Information Generator
Our model used ResNet-50, ResNet-101, and DenseNet-121 convolutional neural networks in order to classify images of food and encode their features, then uses K-nearest neighbors to output …
Lecture 13: Intro To Networking CS110 Spring 2021 - Stanford …
Roslyn Michelle Cyrus | Stanford University 4 Networking Every computer on a network has a unique IP address that identifies it on the network. When you want to connect to a server, you …
Final Exam - Stanford University
f) (2 points) What two factors do computer scientists look at to determine if an algorithm is good (with respect to input size)? Space and time g) (2 points) Recall that computer vision describes …
Computer Science 101 By Stanford University (book)
undergraduates and graduate students in computer science Based on feedback from extensive classroom experience the book has been carefully structured in order to make teaching more …
CS110 Lecture 1: Introduction - Stanford University
CS110A is an extra 1-unit “Pathfinders” or “ACE” section with additional course support, practice and instruction. The goal is to offer an approachable and engaging exposure to effective, …
CS144 – Introduction to Computer Networking - Stanford …
What is a computer network? Why study computer networks? Nodes: Computers, dedicated routers, . . . Links: Coax, twisted pair, fibers, radio . . . ... But how do you build something like …
Stanford Damjan Ostrelič STATEMENT OF …
computer science 101 please note: some online courses may draw on material from courses taught on-campus but they are not equivalent to on-campus courses. this statement does not …
Stanford University | CS103: Math for Computer Science …
Stanford University | CS103: Math for Computer Science Handout PF Luca Trevisan 5/31/2014 Practice Final Problem 1 ... 101 = fjL(M) contains the string \101"g 1. is undecidable. …
Computer Science 101 By Stanford University Copy
Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends It examines drivers of the …
Stanford WON SEOB SEO STATEMENT OF …
computer science 101 please note: some online courses may draw on material from courses taught on-campus but they are not equivalent to on-campus courses. this statement does not …
STANFORD UNIVERSITY SCHOOL OF ENGINEERING
Transfer credits in Math, Science, Fundamentals, and TIS must Student Affairs in Terman 201. Transfer credits in Computer departmental representative. Courses may be listed under only …
CS111, Lecture 1 - Stanford University
•Initially, computers were just one user a time, working directly at a computer. “OSes” were just I/O libraries shared by users for convenience and efficiency. •Over time, computers became …
Suggested Reading 1. Introduction to Computers
Knowing computer: Basic Applications of Computer; Components of Computer System, Central Processing Unit (CPU), VDU, Keyboard and Mouse, Other input/output Devices, Computer …
CS144 – Introduction to Computer Networking - Stanford …
telephone, computer • What is a computer network? - A form of communication network—moves information - Nodes are general-purpose computers • Why study computer networks? - Many …
Cursos Gratuitos en Línea – Universidad de Stanford y …
Cursos Gratuitos en Línea – Universidad de Stanford y Desafío Latam Aprovecha la oportunidad de formarte con cursos gratuitos en áreas clave como ciencia de la computación, inteligencia …
Lecture 01: Welcome to CS110: P rinciples of Computer …
Not stocked at Stanford Bookstore b y design. You can buy a copy of it from Amazon if y ou want. "Computer Systems: A Programmer's Perspective", by Bryant and O'Hallaron "Principles of …
Essential C - Stanford University
This Stanford CS Education document tries to summarize all the basic features of the C language. The coverage is pretty quick, so it is most appropriate as review or for someone with some …
INTRODUCTION MACHINE LEARNING - Stanford University
Department of Computer Science Stanford University Stanford, CA 94305 e-mail: nilsson@cs.stanford.edu November 3, 1998 ... 7.6 Relationships Between ILP and Decision …
The Handbook of Artificial Intelligence - Stanford University
These researchers and students, from Stanford and other AI centers, have contributed to Volumes I and II or are now engaged in preparing Volume 111 (being edited by Paul R. Cohen).
CS105: Introduction to Computer Science - Stanford University
Computer Science Dr. Patrick Young Winter 2010 Class Objectives The course objectives are as follows: to give students a strong background in the fundamentals of computer science, to …
RecipeNet: Image to Recipe/Nutritional Information Generator
Our model used ResNet-50, ResNet-101, and DenseNet-121 convolutional neural networks in order to classify images of food and encode their features, then uses K-nearest neighbors to …
Lecture 13: Intro To Networking CS110 Spring 2021
Roslyn Michelle Cyrus | Stanford University 4 Networking Every computer on a network has a unique IP address that identifies it on the network. When you want to connect to a server, you …
Final Exam - Stanford University
f) (2 points) What two factors do computer scientists look at to determine if an algorithm is good (with respect to input size)? Space and time g) (2 points) Recall that computer vision describes …
