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| double major computer science: Differential Equations and Numerical Analysis Valarmathi Sigamani, John J. H. Miller, Ramanujam Narasimhan, Paramasivam Mathiazhagan, Franklin Victor, 2016-08-18 This book offers an ideal introduction to singular perturbation problems, and a valuable guide for researchers in the field of differential equations. It also includes chapters on new contributions to both fields: differential equations and singular perturbation problems. Written by experts who are active researchers in the related fields, the book serves as a comprehensive source of information on the underlying ideas in the construction of numerical methods to address different classes of problems with solutions of different behaviors, which will ultimately help researchers to design and assess numerical methods for solving new problems. All the chapters presented in the volume are complemented by illustrations in the form of tables and graphs. |
| double major computer science: 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. |
| double major computer science: Data Structures and Algorithm Analysis in Java, Third Edition Clifford A. Shaffer, 2012-09-06 Comprehensive treatment focuses on creation of efficient data structures and algorithms and selection or design of data structure best suited to specific problems. This edition uses Java as the programming language. |
| double major computer science: Computer Science Illuminated Nell B. Dale, John Lewis, 2013 Revised and updated with the latest information in the field, the Fifth Edition of best-selling Computer Science Illuminated continues to provide students with an engaging breadth-first overview of computer science principles and provides a solid foundation for those continuing their study in this dynamic and exciting discipline. Authored by two of today's most respected computer science educators, Nell Dale and John Lewis, the text carefully unfolds the many layers of computing from a language-neutral perspective, beginning with the information layer, progressing through the hardware, programming, operating systems, application, and communication layers, and ending with a discussion on the limitations of computing. Separate program language chapters are available as bundle items for instructors who would like to explore a particular programming language with their students. Ideal for introductory computing and computer science courses, the fifth edition's thorough presentation of computing systems provides computer science majors with a solid foundation for further study, and offers non-majors a comprehensive and complete introduction to computing. New Features of the Fifth Edition: - Includes a NEW chapter on computer security (chapter 17) to provide readers with the latest information, including discussions on preventing unauthorized access and guidelines for creating effective passwords, types of malware anti-virus software, problems created by poor programming, protecting your online information including data collection issues with Facebook, Google, etc., and security issues with mobile and portable devices. - A NEW section on cloud computing (chapter 15) offers readers an overview of the latest way in which businesses and users interact with computers and mobile devices. - The section on social networks (moved to chapter 16) has been rewritten to include up-to-date information, including new data on Google+ and Facebook. - The sections covering HTML have been updated to include HTML5. - Includes revised and updated Did You Know callouts in the chapter margins. - The updated Ethical Issues at the end of each chapter have been revised to tie the content to the recently introduced tenth strand recommended by the ACM stressing the importance of computer ethics. Instructor Resources: -Answers to the end of chapter exercises -Answers to the lab exercises -PowerPoint Lecture Outlines -PowerPoint Image Bank -Test Bank Every new copy is packaged with a free access code to the robust Student Companion Website featuring: Animated Flashcards; Relevant Web Links; Crossword Puzzles; Interactive Glossary; Step by step tutorial on web page development; Digital Lab Manual; R. Mark Meyer's labs, Explorations in Computer Science; Additional programming chapters, including Alice, C++, Java, JavaScript, Pascal, Perl, Python, Ruby, SQL, and VB.NET; C++ Language Essentials labs; Java Language Essentials labs; Link to Download Pep/8 |
| double major computer science: The College Solution Lynn O'Shaughnessy, 2008-06-06 “The College Solution helps readers look beyond over-hyped admission rankings to discover schools that offer a quality education at affordable prices. Taking the guesswork out of saving and finding money for college, this is a practical and insightful must-have guide for every parent!” —Jaye J. Fenderson, Seventeen’s College Columnist and Author, Seventeen’s Guide to Getting into College “This book is a must read in an era of rising tuition and falling admission rates. O’Shaughnessy offers good advice with blessed clarity and brevity.” —Jay Mathews, Washington Post Education Writer and Columnist “I would recommend any parent of a college-bound student read The College Solution.” —Kal Chany, Author, The Princeton Review’s Paying for College Without Going Broke “The College Solution goes beyond other guidebooks in providing an abundance of information about how to afford college, in addition to how to approach the selection process by putting the student first.” —Martha “Marty” O’Connell, Executive Director, Colleges That Change Lives “Lynn O’Shaughnessy always focuses on what’s in the consumer’s best interest, telling families how to save money and avoid making costly mistakes.” —Mark Kantrowitz, Publisher, FinAid.org and Author, FastWeb College Gold “An antidote to the hype and hysteria about getting in and paying for college! O’Shaughnessy has produced an excellent overview that demystifies the college planning process for students and families.” —Barmak Nassirian, American Association of Collegiate Registrars and Admissions Officers For millions of families, the college planning experience has become extremely stressful. And, unless your child is an elite student in the academic top 1%, most books on the subject won’t help you. Now, however, there’s a college guide for everyone. In The College Solution, top personal finance journalist Lynn O’Shaughnessy presents an easy-to-use roadmap to finding the right college program (not just the most hyped) and dramatically reducing the cost of college, too. Forget the rankings! Discover what really matters: the quality and value of the programs your child wants and deserves. O’Shaughnessy uncovers “industry secrets” on how colleges actually parcel out financial aid—and how even “average” students can maximize their share. Learn how to send your kids to expensive private schools for virtually the cost of an in-state public college...and how promising students can pay significantly less than the “sticker price” even at the best state universities. No other book offers this much practical guidance on choosing a college...and no other book will save you as much money! • Secrets your school’s guidance counselor doesn’t know yet The surprising ways colleges have changed how they do business • Get every dime of financial aid that’s out there for you Be a “fly on the wall” inside the college financial aid office • U.S. News & World Report: clueless about your child Beyond one-size-fits-all rankings: finding the right program for your teenager • The best bargains in higher education Overlooked academic choices that just might be perfect for you |
| double major computer science: Fundamentals of Discrete Math for Computer Science Tom Jenkyns, Ben Stephenson, 2012-10-16 This textbook provides an engaging and motivational introduction to traditional topics in discrete mathematics, in a manner specifically designed to appeal to computer science students. The text empowers students to think critically, to be effective problem solvers, to integrate theory and practice, and to recognize the importance of abstraction. Clearly structured and interactive in nature, the book presents detailed walkthroughs of several algorithms, stimulating a conversation with the reader through informal commentary and provocative questions. Features: no university-level background in mathematics required; ideally structured for classroom-use and self-study, with modular chapters following ACM curriculum recommendations; describes mathematical processes in an algorithmic manner; contains examples and exercises throughout the text, and highlights the most important concepts in each section; selects examples that demonstrate a practical use for the concept in question. |
| double major computer science: Python Programming John M. Zelle, 2004 This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic. |
| double major computer science: Concrete Mathematics Ronald L. Graham, Donald E. Knuth, Oren Patashnik, 1994-02-28 This book introduces the mathematics that supports advanced computer programming and the analysis of algorithms. The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data. It is an indispensable text and reference not only for computer scientists - the authors themselves rely heavily on it! - but for serious users of mathematics in virtually every discipline. Concrete Mathematics is a blending of CONtinuous and disCRETE mathematics. More concretely, the authors explain, it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems. The subject matter is primarily an expansion of the Mathematical Preliminaries section in Knuth's classic Art of Computer Programming, but the style of presentation is more leisurely, and individual topics are covered more deeply. Several new topics have been added, and the most significant ideas have been traced to their historical roots. The book includes more than 500 exercises, divided into six categories. Complete answers are provided for all exercises, except research problems, making the book particularly valuable for self-study. Major topics include: Sums Recurrences Integer functions Elementary number theory Binomial coefficients Generating functions Discrete probability Asymptotic methods This second edition includes important new material about mechanical summation. In response to the widespread use of the first edition as a reference book, the bibliography and index have also been expanded, and additional nontrivial improvements can be found on almost every page. Readers will appreciate the informal style of Concrete Mathematics. Particularly enjoyable are the marginal graffiti contributed by students who have taken courses based on this material. The authors want to convey not only the importance of the techniques presented, but some of the fun in learning and using them. |
| double major computer science: Atlas of the Sky Vincent de Callataÿ, 1958 |
| double major computer science: Building Problem Solvers Kenneth D. Forbus, Johan De Kleer, 1993 After working through Building Problem Solvers, readers should have a deep understanding of pattern directed inference systems, constraint languages, and truth maintenance systems. |
| double major computer science: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| double major computer science: The Ultimate Algorithmic Trading System Toolbox + Website George Pruitt, 2016-06-20 The accessible, beneficial guide to developing algorithmic trading solutions The Ultimate Algorithmic Trading System Toolbox is the complete package savvy investors have been looking for. An integration of explanation and tutorial, this guide takes you from utter novice to out-the-door trading solution as you learn the tools and techniques of the trade. You'll explore the broad spectrum of today's technological offerings, and use several to develop trading ideas using the provided source code and the author's own library, and get practical advice on popular software packages including TradeStation, TradersStudio, MultiCharts, Excel, and more. You'll stop making repetitive mistakes as you learn to recognize which paths you should not go down, and you'll discover that you don't need to be a programmer to take advantage of the latest technology. The companion website provides up-to-date TradeStation code, Excel spreadsheets, and instructional video, and gives you access to the author himself to help you interpret and implement the included algorithms. Algorithmic system trading isn't really all that new, but the technology that lets you program, evaluate, and implement trading ideas is rapidly evolving. This book helps you take advantage of these new capabilities to develop the trading solution you've been looking for. Exploit trading technology without a computer science degree Evaluate different trading systems' strengths and weaknesses Stop making the same trading mistakes over and over again Develop a complete trading solution using provided source code and libraries New technology has enabled the average trader to easily implement their ideas at very low cost, breathing new life into systems that were once not viable. If you're ready to take advantage of the new trading environment but don't know where to start, The Ultimate Algorithmic Trading System Toolbox will help you get on board quickly and easily. |
| double major computer science: The Love Hypothesis Ali Hazelwood, 2021-09-14 The Instant New York Times Bestseller and TikTok Sensation! As seen on THE VIEW! A BuzzFeed Best Summer Read of 2021 When a fake relationship between scientists meets the irresistible force of attraction, it throws one woman's carefully calculated theories on love into chaos. As a third-year Ph.D. candidate, Olive Smith doesn't believe in lasting romantic relationships--but her best friend does, and that's what got her into this situation. Convincing Anh that Olive is dating and well on her way to a happily ever after was always going to take more than hand-wavy Jedi mind tricks: Scientists require proof. So, like any self-respecting biologist, Olive panics and kisses the first man she sees. That man is none other than Adam Carlsen, a young hotshot professor--and well-known ass. Which is why Olive is positively floored when Stanford's reigning lab tyrant agrees to keep her charade a secret and be her fake boyfriend. But when a big science conference goes haywire, putting Olive's career on the Bunsen burner, Adam surprises her again with his unyielding support and even more unyielding...six-pack abs. Suddenly their little experiment feels dangerously close to combustion. And Olive discovers that the only thing more complicated than a hypothesis on love is putting her own heart under the microscope. |
| double major computer science: Ultralearning Scott H. Young, 2019-08-06 Now a Wall Street Journal bestseller. Learn a new talent, stay relevant, reinvent yourself, and adapt to whatever the workplace throws your way. Ultralearning offers nine principles to master hard skills quickly. This is the essential guide to future-proof your career and maximize your competitive advantage through self-education. In these tumultuous times of economic and technological change, staying ahead depends on continual self-education—a lifelong mastery of fresh ideas, subjects, and skills. If you want to accomplish more and stand apart from everyone else, you need to become an ultralearner. The challenge of learning new skills is that you think you already know how best to learn, as you did as a student, so you rerun old routines and old ways of solving problems. To counter that, Ultralearning offers powerful strategies to break you out of those mental ruts and introduces new training methods to help you push through to higher levels of retention. Scott H. Young incorporates the latest research about the most effective learning methods and the stories of other ultralearners like himself—among them Benjamin Franklin, chess grandmaster Judit Polgár, and Nobel laureate physicist Richard Feynman, as well as a host of others, such as little-known modern polymath Nigel Richards, who won the French World Scrabble Championship—without knowing French. Young documents the methods he and others have used to acquire knowledge and shows that, far from being an obscure skill limited to aggressive autodidacts, ultralearning is a powerful tool anyone can use to improve their career, studies, and life. Ultralearning explores this fascinating subculture, shares a proven framework for a successful ultralearning project, and offers insights into how you can organize and exe - cute a plan to learn anything deeply and quickly, without teachers or budget-busting tuition costs. Whether the goal is to be fluent in a language (or ten languages), earn the equivalent of a college degree in a fraction of the time, or master multiple tools to build a product or business from the ground up, the principles in Ultralearning will guide you to success. |
| double major computer science: Gödel, Escher, Bach Douglas R. Hofstadter, 2000 'What is a self and how can a self come out of inanimate matter?' This is the riddle that drove Douglas Hofstadter to write this extraordinary book. In order to impart his original and personal view on the core mystery of human existence - our intangible sensation of 'I'-ness - Hofstadter defines the playful yet seemingly paradoxical notion of 'strange loop', and explicates this idea using analogies from many disciplines. |
| double major computer science: Coding the Matrix Philip N. Klein, 2013-07 An engaging introduction to vectors and matrices and the algorithms that operate on them, intended for the student who knows how to program. Mathematical concepts and computational problems are motivated by applications in computer science. The reader learns by doing, writing programs to implement the mathematical concepts and using them to carry out tasks and explore the applications. Examples include: error-correcting codes, transformations in graphics, face detection, encryption and secret-sharing, integer factoring, removing perspective from an image, PageRank (Google's ranking algorithm), and cancer detection from cell features. A companion web site, codingthematrix.com provides data and support code. Most of the assignments can be auto-graded online. Over two hundred illustrations, including a selection of relevant xkcd comics. Chapters: The Function, The Field, The Vector, The Vector Space, The Matrix, The Basis, Dimension, Gaussian Elimination, The Inner Product, Special Bases, The Singular Value Decomposition, The Eigenvector, The Linear Program A new edition of this text, incorporating corrections and an expanded index, has been issued as of September 4, 2013, and will soon be available on Amazon. |
| double major computer science: A Programmer's Guide to Computer Science William M Springer II, 2020-01-03 You know how to code..but is it enough? Do you feel left out when other programmers talk about asymptotic bounds? Have you failed a job interview because you don't know computer science? The author, a senior developer at a major software company with a PhD in computer science, takes you through what you would have learned while earning a four-year computer science degree. Volume one covers the most frequently referenced topics, including algorithms and data structures, graphs, problem-solving techniques, and complexity theory. When you finish this book, you'll have the tools you need to hold your own with people who have - or expect you to have - a computer science degree. |
| double major computer science: Fahrenheit 451 Ray Bradbury, 1968 A fireman in charge of burning books meets a revolutionary school teacher who dares to read. Depicts a future world in which all printed reading material is burned. |
| double major computer science: Cracking the PM Interview Gayle Laakmann McDowell, Jackie Bavaro, 2013 How many pizzas are delivered in Manhattan? How do you design an alarm clock for the blind? What is your favorite piece of software and why? How would you launch a video rental service in India? This book will teach you how to answer these questions and more. Cracking the PM Interview is a comprehensive book about landing a product management role in a startup or bigger tech company. Learn how the ambiguously-named PM (product manager / program manager) role varies across companies, what experience you need, how to make your existing experience translate, what a great PM resume and cover letter look like, and finally, how to master the interview: estimation questions, behavioral questions, case questions, product questions, technical questions, and the super important pitch. |
| double major computer science: Design Automation of Cyber-Physical Systems Mohammad Abdullah Al Faruque, Arquimedes Canedo, 2019-05-09 This book presents the state-of-the-art and breakthrough innovations in design automation for cyber-physical systems.The authors discuss various aspects of cyber-physical systems design, including modeling, co-design, optimization, tools, formal methods, validation, verification, and case studies. Coverage includes a survey of the various existing cyber-physical systems functional design methodologies and related tools will provide the reader unique insights into the conceptual design of cyber-physical systems. |
| double major computer science: Java Programming Ralph Bravaco, Shai Simonson, 2009-02-01 Java Programming, From The Ground Up, with its flexible organization, teaches Java in a way that is refreshing, fun, interesting and still has all the appropriate programming pieces for students to learn. The motivation behind this writing is to bring a logical, readable, entertaining approach to keep your students involved. Each chapter has a Bigger Picture section at the end of the chapter to provide a variety of interesting related topics in computer science. The writing style is conversational and not overly technical so it addresses programming concepts appropriately. Because of the flexibile organization of the text, it can be used for a one or two semester introductory Java programming class, as well as using Java as a second language. The text contains a large variety of carefully designed exercises that are more effective than the competition. |
| double major computer science: A Computational Approach to Statistical Learning Taylor Arnold, Michael Kane, Bryan W. Lewis, 2019-01-23 A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal working implementations of common statistical learning algorithms. Every chapter concludes with a fully worked out application that illustrates predictive modeling tasks using a real-world dataset. The text begins with a detailed analysis of linear models and ordinary least squares. Subsequent chapters explore extensions such as ridge regression, generalized linear models, and additive models. The second half focuses on the use of general-purpose algorithms for convex optimization and their application to tasks in statistical learning. Models covered include the elastic net, dense neural networks, convolutional neural networks (CNNs), and spectral clustering. A unifying theme throughout the text is the use of optimization theory in the description of predictive models, with a particular focus on the singular value decomposition (SVD). Through this theme, the computational approach motivates and clarifies the relationships between various predictive models. Taylor Arnold is an assistant professor of statistics at the University of Richmond. His work at the intersection of computer vision, natural language processing, and digital humanities has been supported by multiple grants from the National Endowment for the Humanities (NEH) and the American Council of Learned Societies (ACLS). His first book, Humanities Data in R, was published in 2015. Michael Kane is an assistant professor of biostatistics at Yale University. He is the recipient of grants from the National Institutes of Health (NIH), DARPA, and the Bill and Melinda Gates Foundation. His R package bigmemory won the Chamber's prize for statistical software in 2010. Bryan Lewis is an applied mathematician and author of many popular R packages, including irlba, doRedis, and threejs. |
| double major computer science: The Real Wealth of Nations Riane Eisler, 2008-11-10 Bestselling author Riane Eisler (The Chalice and the Blade, which has sold more than 500,000 copies sold) shows that at the root of all of society's big problems is the fact that we don't value what matters. She then presents a radical reformulation of economics priorities focused on the home. |
| double major computer science: Principles of Mathematics Carl Barnett Allendoerfer, Cletus Odia Oakley, 1953 |
| double major computer science: Vis Enviro Science EPUB High School 6 Year Access David M. Hassenzahl, Linda R. Berg, Mary Catherine Hager, 2017-11-06 |
| double major computer science: The Self-Taught Computer Scientist Cory Althoff, 2021-09-16 The follow-up to Cory Althoff's bestselling The Self-Taught Programmer, which inspired hundreds of thousands of professionals to learn to program outside of school! Fresh out of college and with just a year of self-study behind him, Cory Althoff was offered a dream first job as a software engineer for a well-known tech company, but he quickly found himself overwhelmed by the amount of things he needed to know, but hadn’t learned yet. This experience combined with his personal journey learning to program inspired his widely praised guide, The Self-Taught Programmer. Now Cory's back with another guide for the self-taught community of learners focusing on the foundations of computer science. The Self-Taught Computer Scientist introduces beginner and self-taught programmers to computer science fundamentals that are essential for success in programming and software engineering fields. Computer science is a massive subject that could cover an entire lifetime of learning. This book does not aim to cover everything you would learn about if you went to school to get a computer science degree. Instead, Cory's goal is to give you an introduction to some of the most important concepts in computer science that apply to a programming career. With a focus on data structures and algorithms, The Self-Taught Computer Scientist helps you fill gaps in your knowledge, prepare for a technical interview, feel knowledgeable and confident on the job, and ultimately, become a better programmer. Learn different algorithms including linear and binary search and test your knowledge with feedback loops Understand what a data structure is and study arrays, linked lists, stacks, queues, hash tables, binary trees, binary heaps, and graphs Prepare for technical interviews and feel comfortable working with more experienced colleagues Discover additional resources and tools to expand your skillset and continue your learning journey It's as simple as this: You have to study computer science if you want to become a successful programmer, and if you don't understand computer science, you won't get hired. Ready for a career in programming, coding, or software engineering and willing to embrace an always be learning mindset? The Self-Taught Computer Scientist is for you. |
| double major computer science: How to Be a High School Superstar Cal Newport, 2010-07-27 Do Less, Live More, Get Accepted What if getting into your reach schools didn’t require four years of excessive A.P. classes, overwhelming activity schedules, and constant stress? In How to Be a High School Superstar, Cal Newport explores the world of relaxed superstars—students who scored spots at the nation’s top colleges by leading uncluttered, low stress, and authentic lives. Drawing from extensive interviews and cutting-edge science, Newport explains the surprising truths behind these superstars’ mixture of happiness and admissions success, including: · Why doing less is the foundation for becoming more impressive. · Why demonstrating passion is meaningless, but being interesting is crucial. · Why accomplishments that are hard to explain are better than accomplishments that are hard to do. These insights are accompanied by step-by-step instructions to help any student adopt the relaxed superstar lifestyle—proving that getting into college doesn’t have to be a chore to survive, but instead can be the reward for living a genuinely interesting life. |
| double major computer science: 101 Careers in Mathematics: Fourth Edition Deanna Haunsperger, Robert Thompson, 2019-09-24 What can you do with a degree in math? This book addresses this question with 125 career profiles written by people with degrees and backgrounds in mathematics. With job titles ranging from sports analyst to science writer to inventory specialist to CEO, the volume provides ample evidence that one really can do nearly anything with a degree in mathematics. These professionals share how their mathematical education shaped their career choices and how mathematics, or the skills acquired in a mathematics education, is used in their daily work. The degrees earned by the authors profiled here are a good mix of bachelors, masters, and PhDs. With 114 completely new profiles since the third edition, the careers featured within accurately reflect current trends in the job market. College mathematics faculty, high school teachers, and career counselors will all find this a useful resource. Career centers, mathematics departments, and student lounges should have a copy available for student browsing. In addition to the career profiles, the volume contains essays from career counseling professionals on the topics of job-searching, interviewing, and applying to graduate school. |
| double major computer science: 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. |
| double major computer science: Bridging Linguistics and Economics Cécile B. Vigouroux, Salikoko S. Mufwene, 2020-03-19 By bridging the gap between linguistics and economics, this book sheds light on a range of mutually valuable topics. |
| double major computer science: 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 |
| double major computer science: Mechanical And Electronics Engineering - Proceedings Of The International Conference On Icmee 2009 Venkatesh Mahadevan, Jianhong Zhou, 2009-07-16 The 2009 International Conference on Mechanical and Electronics Engineering (ICMEE 2009) will be held in Chennai, India from 24-26 July, 2009. The aim of ICMEE 2009 is to provide a platform for researchers, engineers, academicians as well as industrial professionals from all over the world to present their research findings and development activities in mechanical and electronics engineering. This conference provides opportunities for the delegates to exchange new ideas and application experiences face to face, to forge new business or research relations and to find global partners for future collaboration. |
| double major computer science: Introduction to Data Systems Thomas Bressoud, David White, 2020-12-04 Encompassing a broad range of forms and sources of data, this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files, then progresses to data acquired from relational databases, from REST APIs and through web scraping. It teaches data forms/formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure, operations, and constraints of each data form. The starting point of the book is a foundation in Python programming found in introductory computer science classes or short courses on the language, and so does not require prerequisites of data structures, algorithms, or other courses. This makes the material accessible to students early in their educational career and equips them with understanding and skills that can be applied in computer science, data science/data analytics, and information technology programs as well as for internships and research experiences. This book is accessible to a wide variety of students. By drawing together content normally spread across upper level computer science courses, it offers a single source providing the essentials for data science practitioners. In our increasingly data-centric world, students from all domains will benefit from the “data-aptitude” built by the material in this book. |
| double major computer science: Doing Data Science Cathy O'Neil, Rachel Schutt, 2013-10-09 Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. |
| double major computer science: Introduction To Computational Mathematics (2nd Edition) Xin-she Yang, 2014-11-26 This unique book provides a comprehensive introduction to computational mathematics, which forms an essential part of contemporary numerical algorithms, scientific computing and optimization. It uses a theorem-free approach with just the right balance between mathematics and numerical algorithms. This edition covers all major topics in computational mathematics with a wide range of carefully selected numerical algorithms, ranging from the root-finding algorithm, numerical integration, numerical methods of partial differential equations, finite element methods, optimization algorithms, stochastic models, nonlinear curve-fitting to data modelling, bio-inspired algorithms and swarm intelligence. This book is especially suitable for both undergraduates and graduates in computational mathematics, numerical algorithms, scientific computing, mathematical programming, artificial intelligence and engineering optimization. Thus, it can be used as a textbook and/or reference book. |
| double major computer science: American Universities in a Global Market Charles T. Clotfelter, 2010-06-15 In higher education, the United States is the preeminent global leader, dominating the list of the world’s top research universities. But there are signs that America’s position of global leadership will face challenges in the future, as it has in other realms of international competition. American Universities in a Global Market addresses the variety of issues crucial to understanding this preeminence and this challenge. The book examines the various factors that contributed to America’s success in higher education, including openness to people and ideas, generous governmental support, and a tradition of decentralized friendly competition. It also explores the advantages of holding a dominant position in this marketplace and examines the current state of American higher education in a comparative context, placing particular emphasis on how market forces affect universities. By discussing the differences in quality among students and institutions around the world, this volume sheds light on the singular aspects of American higher education. |
| double major computer science: A Programmer's Introduction to Mathematics Jeremy Kun, 2020-05-17 A Programmer's Introduction to Mathematics uses your familiarity with ideas from programming and software to teach mathematics. You'll learn about the central objects and theorems of mathematics, including graphs, calculus, linear algebra, eigenvalues, optimization, and more. You'll also be immersed in the often unspoken cultural attitudes of mathematics, learning both how to read and write proofs while understanding why mathematics is the way it is. Between each technical chapter is an essay describing a different aspect of mathematical culture, and discussions of the insights and meta-insights that constitute mathematical intuition. As you learn, we'll use new mathematical ideas to create wondrous programs, from cryptographic schemes to neural networks to hyperbolic tessellations. Each chapter also contains a set of exercises that have you actively explore mathematical topics on your own. In short, this book will teach you to engage with mathematics. A Programmer's Introduction to Mathematics is written by Jeremy Kun, who has been writing about math and programming for 10 years on his blog Math Intersect Programming. As of 2020, he works in datacenter optimization at Google.The second edition includes revisions to most chapters, some reorganized content and rewritten proofs, and the addition of three appendices. |
| double major computer science: The Architecture of Symbolic Computers Peter M. Kogge, 1991 Focuses on the design and implementation of two classes of non-von Neumann computer architecture: those designed for functional and logical language computing. |
| double major computer science: How to Win at College : Surprising Secrets for Success from the Country's Top Students Cal Newport, 2005 |
| double major computer science: Foundation Maths Anthony Croft, Robert Davison, 2011-09-21 Were you looking for the book with access to MyMathLab? This product is the book alone, and does NOT come with access to MyMathLab. Buy Foundation Maths with MyMathLab access card 5e (ISBN 9780273730767) if you need access to the MyLab as well, and save money on this brilliant resource. Foundation Maths has been written for students taking higher and further education courses who have not specialised in mathematics on post-16 qualifications and need to use mathematical tools in their courses. It is ideally suited to those studying marketing, business studies, management, science, engineering, social science, geography, combined studies and design. It will be useful for those who lack confidence and who need careful, steady guidance in mathematical methods. For those whose mathematical expertise is already established, the book will be a helpful revision and reference guide. The style of the book also makes it suitable for self-study and distance learning. Need extra support? This product is the book alone, and does NOT come with access to MyMathLab. This title can be supported by MyMathLab, an online homework and tutorial system which can be fully integrated into an instructor's course. You can benefit from MyMathLab at a reduced price by purchasing a pack containing a copy of the book and an access card for MyMathLab: Foundation Maths with MyMathLab access card 5e (ISBN 9780273730767). Alternatively, buy access to MyMathLab and the eText – an online version of the book - online at www.mymathlab.com. For educator access, contact your Pearson Account Manager. To find out who your Account Manager is, visit www.pearsoned.co.uk/replocator |
What is the difference between float and double? - Stack Overflow
Dec 31, 2021 · Type double, 64 bits long, has a bigger range (*10^+/-308) and 15 digits precision. Type long double is nominally 80 bits, though a given compiler/OS pairing may store it as 12 …
How do I print a double value with full precision using cout?
Dec 17, 2020 · A double is a floating point type, not fixed point. Do not use std::fixed as that fails to print small double as anything but 0.000...000. For large double, it prints many digits, …
Difference between long double and double in C and C++
Apr 22, 2015 · The standard only requires that long double is at least as precise as double, so some compilers will simply treat long double as if it is the same as double. But, on most x86 …
Correct format specifier for double in printf - Stack Overflow
Format %lf is a perfectly correct printf format for double, exactly as you used it. There's nothing wrong with your code. There's nothing wrong with your code. Format %lf in printf was not …
Reading in double values with scanf in c - Stack Overflow
Oct 7, 2017 · I found out that there is a problem with the length of double on 32 bit OS, so that you are forced to use scanf("%lf", &f) to read in a double. No matter what I do, second value is …
decimal vs double! - Which one should I use and when?
Jul 22, 2009 · To clear this up double does not have 16 digits - that is only the number of meaningful digits. Floats are based around exponents in base 2 math - some base 10 …
How to Code Double Quotes via HTML Codes - Stack Overflow
Feb 28, 2013 · I was just curious as to why there needs to be 3 different ways to code a double quotes in html codes, for example. – H. Ferrence Commented Feb 28, 2013 at 12:48
Difference between decimal, float and double in .NET?
Mar 6, 2009 · Double: It is also a floating binary point type variable with double precision and 64 bits size(15-17 significant figures). Double are probably the most generally used data type for …
What is the size of float and double in C and C++? [duplicate]
Aug 27, 2014 · The set of values of the type float is a subset of the set of values of the type double; the set of values of the type double is a subset of the set of values of the type long …
What does the !! (double exclamation mark) operator do in …
The double negation operator !! calculates the truth value of a value. It's actually two operators, where !!x means !(!x), and behaves as follows: If x is a false value, !x is true, and !!x is false. If …
What is the difference between float and double? - Stack Overflow
Dec 31, 2021 · Type double, 64 bits long, has a bigger range (*10^+/-308) and 15 digits precision. Type long double is nominally 80 bits, though a given compiler/OS pairing may store it as 12 …
How do I print a double value with full precision using cout?
Dec 17, 2020 · A double is a floating point type, not fixed point. Do not use std::fixed as that fails to print small double as anything but 0.000...000. For large double, it prints many digits, …
Difference between long double and double in C and C++
Apr 22, 2015 · The standard only requires that long double is at least as precise as double, so some compilers will simply treat long double as if it is the same as double. But, on most x86 …
Correct format specifier for double in printf - Stack Overflow
Format %lf is a perfectly correct printf format for double, exactly as you used it. There's nothing wrong with your code. There's nothing wrong with your code. Format %lf in printf was not …
Reading in double values with scanf in c - Stack Overflow
Oct 7, 2017 · I found out that there is a problem with the length of double on 32 bit OS, so that you are forced to use scanf("%lf", &f) to read in a double. No matter what I do, second value is …
decimal vs double! - Which one should I use and when?
Jul 22, 2009 · To clear this up double does not have 16 digits - that is only the number of meaningful digits. Floats are based around exponents in base 2 math - some base 10 …
How to Code Double Quotes via HTML Codes - Stack Overflow
Feb 28, 2013 · I was just curious as to why there needs to be 3 different ways to code a double quotes in html codes, for example. – H. Ferrence Commented Feb 28, 2013 at 12:48
Difference between decimal, float and double in .NET?
Mar 6, 2009 · Double: It is also a floating binary point type variable with double precision and 64 bits size(15-17 significant figures). Double are probably the most generally used data type for …
What is the size of float and double in C and C++? [duplicate]
Aug 27, 2014 · The set of values of the type float is a subset of the set of values of the type double; the set of values of the type double is a subset of the set of values of the type long …
What does the !! (double exclamation mark) operator do in …
The double negation operator !! calculates the truth value of a value. It's actually two operators, where !!x means !(!x), and behaves as follows: If x is a false value, !x is true, and !!x is false. If …
