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| course outline for computer science: Princeton Review AP Computer Science A Prep, 2022 The Princeton Review, 2021-08-31 Make sure you’re studying with the most up-to-date prep materials! Look for the newest edition of this title, The Princeton Review AP Computer Science A Prep, 2023 (ISBN: 9780593450727, on-sale September 2020). Publisher's Note: Products purchased from third-party sellers are not guaranteed by the publisher for quality or authenticity, and may not include access to online tests or materials included with the original product. |
| course outline for computer science: Understanding by Design Grant P. Wiggins, Jay McTighe, 2005 What is understanding and how does it differ from knowledge? How can we determine the big ideas worth understanding? Why is understanding an important teaching goal, and how do we know when students have attained it? How can we create a rigorous and engaging curriculum that focuses on understanding and leads to improved student performance in today's high-stakes, standards-based environment? Authors Grant Wiggins and Jay McTighe answer these and many other questions in this second edition of Understanding by Design. Drawing on feedback from thousands of educators around the world who have used the UbD framework since its introduction in 1998, the authors have greatly revised and expanded their original work to guide educators across the K-16 spectrum in the design of curriculum, assessment, and instruction. With an improved UbD Template at its core, the book explains the rationale of backward design and explores in greater depth the meaning of such key ideas as essential questions and transfer tasks. Readers will learn why the familiar coverage- and activity-based approaches to curriculum design fall short, and how a focus on the six facets of understanding can enrich student learning. With an expanded array of practical strategies, tools, and examples from all subject areas, the book demonstrates how the research-based principles of Understanding by Design apply to district frameworks as well as to individual units of curriculum. Combining provocative ideas, thoughtful analysis, and tested approaches, this new edition of Understanding by Design offers teacher-designers a clear path to the creation of curriculum that ensures better learning and a more stimulating experience for students and teachers alike. |
| course outline for computer science: Introduction to Programming in Java: An Interdisciplinary Approach Robert Sedgewick, Kevin Wayne, 2013-07-31 By emphasizing the application of computer programming not only in success stories in the software industry but also in familiar scenarios in physical and biological science, engineering, and applied mathematics, Introduction to Programming in Java takes an interdisciplinary approach to teaching programming with the Java(TM) programming language. Interesting applications in these fields foster a foundation of computer science concepts and programming skills that students can use in later courses while demonstrating that computation is an integral part of the modern world. Ten years in development, this book thoroughly covers the field and is ideal for traditional introductory programming courses. It can also be used as a supplement or a main text for courses that integrate programming with mathematics, science, or engineering. |
| course outline for computer science: Multimedia Information Systems V.S. Subrahmanian, Satish K. Tripathi, 1998-06-30 Multimedia Information Systems brings together in one place important contributions and up-to-date research results in this fast moving area. Multimedia Information Systems serves as an excellent reference, providing insight into some of the most challenging research issues in the field. |
| course outline for 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. |
| course outline for computer science: Introduction to Computation and Programming Using Python, second edition John V. Guttag, 2016-08-12 The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics. |
| course outline for computer science: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| course outline for computer science: Schaum's Outline of Introduction to Computer Science Ramon A. Mata-Toledo, Pauline K. Cushman, 1999 Illustrates key computing concepts using examples in the most popular programming languages. This is an essential guide for the hundreds of thousands of students studying Introduction to Computer Science or Introduction to Programming, presenting the basic concepts of computerscience and illlustrating them with examples in C/C++, and Java. More than 285,000 college majors and 11,000 high school Advanced Placement candidates are enrolled in required Computing Science courses. Explains algorithm development and data abstraction. Supplements leading computer science textbooks. |
| course outline for computer science: Numerical Methods in Engineering with Python 3 Jaan Kiusalaas, 2013-01-21 Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language. |
| course outline for computer science: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| course outline for computer science: The Carnegie-Mellon Curriculum for Undergraduate Computer Science Mary Shaw, 1985 This curriculum and its description were developed during the period 1981 - 1984 |
| course outline for computer science: 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. |
| course outline for computer science: AP® Computer Science Principles Crash Course Jacqueline Corricelli, 2018-01-04 AP® Computer Science Principles Crash Course® A Higher Score in Less Time! REA's AP® Computer Science Principles Crash Course® is the top choice for the last-minute studier or any Computer Science Principles student who wants a quick refresher on the course. Are you crunched for time? Have you started studying for your Advanced Placement® Computer Science Principles exam yet? How will you memorize everything you need to know before the test? Do you wish there was a fast and easy way to study for the exam AND boost your score? If this sounds like you, don't panic. REA's Crash Course for AP® Computer Science Principles is just what you need. Our Crash Course gives you: Targeted Review - Study Only What You Need to Know. The review is based on an in-depth analysis of the AP® Computer Science Principles course description outline and sample AP® test questions. It covers only the information tested on the exam, so you can make the most of your valuable study time. Expert Test-taking Strategies and Advice. Written by Jacqueline Corricelli, an award-winning AP® Computer Science Principles teacher and test development expert, the book gives you the topics and critical context that will matter most on exam day. Crash Course® relies on the author’s extensive analysis of the test’s structure and content. By following her advice, you can boost your score. REA's Online Practice Exam. Are you ready for your exam? Take REA's practice exam and find out. You'll get the benefits of timed testing, detailed explanations of answers, and automatic scoring analysis. Our practice exam is balanced to include every topic and type of question found on the actual AP® exam, so you'll be confident on test day. Whether you're cramming for the exam or reinforcing what you learn as you go through the course, this is the study guide every AP® Computer Science Principles student must have. |
| course outline for 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. |
| course outline for computer science: Introduction To Algorithms Thomas H Cormen, Charles E Leiserson, Ronald L Rivest, Clifford Stein, 2001 An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms. |
| course outline for computer science: Discrete Mathematics for Computer Science Gary Haggard, John Schlipf, Sue Whitesides, 2006 Master the fundamentals of discrete mathematics with DISCRETE MATHEMATICS FOR COMPUTER SCIENCE with Student Solutions Manual CD-ROM! An increasing number of computer scientists from diverse areas are using discrete mathematical structures to explain concepts and problems and this mathematics text shows you how to express precise ideas in clear mathematical language. Through a wealth of exercises and examples, you will learn how mastering discrete mathematics will help you develop important reasoning skills that will continue to be useful throughout your career. |
| course outline for computer science: Competing in the Age of AI Marco Iansiti, Karim R. Lakhani, 2020-01-07 a provocative new book — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how collisions between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI. |
| course outline for computer science: National Educational Technology Standards for Students International Society for Technology in Education, 2007 This booklet includes the full text of the ISTE Standards for Students, along with the Essential Conditions, profiles and scenarios. |
| course outline for computer science: Essential Questions Jay McTighe, Grant Wiggins, 2013-03-27 What are essential questions, and how do they differ from other kinds of questions? What's so great about them? Why should you design and use essential questions in your classroom? Essential questions (EQs) help target standards as you organize curriculum content into coherent units that yield focused and thoughtful learning. In the classroom, EQs are used to stimulate students' discussions and promote a deeper understanding of the content. Whether you are an Understanding by Design (UbD) devotee or are searching for ways to address standards—local or Common Core State Standards—in an engaging way, Jay McTighe and Grant Wiggins provide practical guidance on how to design, initiate, and embed inquiry-based teaching and learning in your classroom. Offering dozens of examples, the authors explore the usefulness of EQs in all K-12 content areas, including skill-based areas such as math, PE, language instruction, and arts education. As an important element of their backward design approach to designing curriculum, instruction, and assessment, the authors *Give a comprehensive explanation of why EQs are so important; *Explore seven defining characteristics of EQs; *Distinguish between topical and overarching questions and their uses; *Outline the rationale for using EQs as the focal point in creating units of study; and *Show how to create effective EQs, working from sources including standards, desired understandings, and student misconceptions. Using essential questions can be challenging—for both teachers and students—and this book provides guidance through practical and proven processes, as well as suggested response strategies to encourage student engagement. Finally, you will learn how to create a culture of inquiry so that all members of the educational community—students, teachers, and administrators—benefit from the increased rigor and deepened understanding that emerge when essential questions become a guiding force for learners of all ages. |
| course outline for computer science: Jacob K. Javits Gifted and Talented Students Education Program , 1998 |
| course outline for computer science: The Elements of Computing Systems Noam Nisan, Shimon Schocken, 2008 This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system. |
| course outline for computer science: Software Engineering and Development Enrique A. Belini, 2009 Software engineering is one of the most knowledge intensive jobs. Thus, having a good knowledge management (KM) strategy in these organisations is very important. This book examines software processes from a knowledge perspective flow, in order to identify the particular knowledge needs of such processes to then be in a better position for proposing systems or strategies to address those needs. Its possible benefits are illustrated through the results of a study in a software maintenance process within a small software organisation. Furthermore, software product line architecture is regarded as one of the crucial piece of entity in software product lines. The authors of this book discuss the state of the art of software product line engineering from the perspectives of business, architecture, process and organisation. In recent years, domain-specific languages have been proposed for modelling applications on a high level of abstraction. Although the usage of domain-specific languages offers clear advantages, their design is a highly complex task. This book presents a pragmatic way for designing and using domain-specific languages. Other chapters in this book examine the development of numerical methodologies for inverse determination of material constitutive model parameters, discuss some of the reasons for the irrelevancy of software engineering to the robotic community, review the evolution of robotic software over time, and propose the use of Ant Colony Optimisation, a kind of metaheuristic algorithm, to find general property violations in concurrent systems using a explicit state model checker. |
| course outline for computer science: Blown to Bits Harold Abelson, Ken Ledeen, Harry R. Lewis, 2008 'Blown to Bits' is about how the digital explosion is changing everything. The text explains the technology, why it creates so many surprises and why things often don't work the way we expect them to. It is also about things the information explosion is destroying: old assumptions about who is really in control of our lives. |
| course outline for computer science: Computation Structures Stephen A. Ward, Robert H. Halstead, 1990 Computer Systems Organization -- general. |
| course outline for 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 |
| course outline for computer science: 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. |
| course outline for computer science: Operating Systems Remzi H. Arpaci-Dusseau, Andrea C. Arpaci-Dusseau, 2018-09 This book is organized around three concepts fundamental to OS construction: virtualization (of CPU and memory), concurrency (locks and condition variables), and persistence (disks, RAIDS, and file systems--Back cover. |
| course outline for computer science: Explorations in Computing John S. Conery, 2014-09-24 An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to |
| course outline for computer science: The Carnegie-Mellon Curriculum for Undergraduate Computer Science Mary Shaw, S.D. Brookes, M. Donner, J. Driscoll, M. Mauldin, R. Pausch, W.L. Scherlis, A.Z. Spector, 2012-12-06 This curriculum and its description were developed during the period 1981 - 1984 |
| course outline for computer science: 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 |
| course outline for computer science: Computer Science in Social and Behavioral Science Education Daniel Edgar Bailey, 1978 |
| course outline for computer science: Discrete Mathematics and Computing Malik Magdon-Ismail, 2019-12-14 This text is a semester course in the basic mathematical and theoretical foundations of computer science. Students who make heavy use of computing should learn these foundations well, setting a base for a follow-on course in algorithms. A solid theoretical and algorithmic foundation in computer science sets the stage for developing good programs, programs that work, always and efficiently.Each chapter is a lecture that has been taught as such. Part I starts with basic logic, proofs and discrete mathematics, including: induction, recursion, summation, asymptotics and number theory. We then continue with graphs, counting and combinatorics, and wrap up the coverage of discrete mathematics with discrete probability. Part II presents the blockbuster application of discrete mathematics: the digital computer and a theory of computing. The goal is to understand what a computer can and cannot do. We start small, with automata, and end big with Turing Machines.Our approach is Socratic. The reader is encouraged to participate actively in the learning process by doing the quizzes and exercises that are liberally sprinkled through the text. The pace and level is appropriate for readers with one year of training in programming and calculus (college sophomores). |
| course outline for computer science: CompTIA A+ Complete Practice Tests Jeff T. Parker, Quentin Docter, 2019-07-18 Test your knowledge and know what to expect on A+ exam day CompTIA A+ Complete Practice Tests, Second Edition enables you to hone your test-taking skills, focus on challenging areas, and be thoroughly prepared to ace the exam and earn your A+ certification. This essential component of your overall study plan presents nine unique practice tests—and two 90-question bonus tests—covering 100% of the objective domains for both the 220-1001 and 220-1002 exams. Comprehensive coverage of every essential exam topic ensures that you will know what to expect on exam day and maximize your chances for success. Over 1200 practice questions on topics including hardware, networking, mobile devices, operating systems and procedures, troubleshooting, and more, lets you assess your performance and gain the confidence you need to pass the exam with flying colors. This second edition has been fully updated to reflect the latest best practices and updated exam objectives you will see on the big day. A+ certification is a crucial step in your IT career. Many businesses require this accreditation when hiring computer technicians or validating the skills of current employees. This collection of practice tests allows you to: Access the test bank in the Sybex interactive learning environment Understand the subject matter through clear and accurate answers and explanations of exam objectives Evaluate your exam knowledge and concentrate on problem areas Integrate practice tests with other Sybex review and study guides, including the CompTIA A+ Complete Study Guide and the CompTIA A+ Complete Deluxe Study Guide Practice tests are an effective way to increase comprehension, strengthen retention, and measure overall knowledge. The CompTIA A+ Complete Practice Tests, Second Edition is an indispensable part of any study plan for A+ certification. |
| course outline for computer science: Getting Started with Processing.py Allison Parrish, Ben Fry, Casey Reas, 2016-05-11 Processing opened up the world of programming to artists, designers, educators, and beginners. The Processing.py Python implementation of Processing reinterprets it for today's web. This short book gently introduces the core concepts of computer programming and working with Processing. Written by the co-founders of the Processing project, Reas and Fry, along with co-author Allison Parrish, Getting Started with Processing.py is your fast track to using Python's Processing mode. |
| course outline for computer science: Princeton Review AP Computer Science Principles Prep, 2022 The Princeton Review, 2021-08-03 Make sure you’re studying with the most up-to-date prep materials! Look for the newest edition of this title, The Princeton Review AP Computer Science Principles Prep, 2023 (ISBN: 9780593450734, on-sale August 2022). Publisher's Note: Products purchased from third-party sellers are not guaranteed by the publisher for quality or authenticity, and may not include access to online tests or materials included with the original product. |
| course outline for computer science: Goal-based Decision Making Stephen Slade, 2013-06-17 This work presents a goal-based model of decision making in which the relative priorities of goals drive the decision process -- a psychological alternative to traditional decision analysis. Building on the work of Schank and Abelson, the author uses goals as the basis for a model of interpersonal relations which permits decisions to incorporate personal and adopted goals in a uniform manner. The theory is modelled on the VOTE computer program which simulates Congressional roll-call voting decisions. The VOTE program expands traditional decision making and simulation models by providing not only a choice, but also a natural language explanation, in either English or French. It simulates real members of Congress voting on real bills, and producing reasonable explanations. The program is consistent with much of the descriptive political science literature on Congressional decision making and provides an explicit model of political issues, relationships, and strategies that converge in voting behavior. In developing the VOTE program, the author draws on his own practical experience in politics from four presidential campaigns and the White House. Given the underlying psychological basis of the program, VOTE can be extended to other decision making domains different from politics. Another use for the program is to simulate business decisions such as securities analysis, as well as mundane decision making such as choosing a college or deciding whether to get a Mohawk haircut. |
| course outline for 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 |
| course outline for computer science: Information Storage and Management EMC Education Services, 2012-04-30 The new edition of a bestseller, now revised and update throughout! This new edition of the unparalleled bestseller serves as a full training course all in one and as the world's largest data storage company, EMC is the ideal author for such a critical resource. They cover the components of a storage system and the different storage system models while also offering essential new material that explores the advances in existing technologies and the emergence of the Cloud as well as updates and vital information on new technologies. Features a separate section on emerging area of cloud computing Covers new technologies such as: data de-duplication, unified storage, continuous data protection technology, virtual provisioning, FCoE, flash drives, storage tiering, big data, and more Details storage models such as Network Attached Storage (NAS), Storage Area Network (SAN), Object Based Storage along with virtualization at various infrastructure components Explores Business Continuity and Security in physical and virtualized environment Includes an enhanced Appendix for additional information This authoritative guide is essential for getting up to speed on the newest advances in information storage and management. |
| course outline for computer science: AP® Computer Science Principles Crash Course, 2nd Ed., Book + Online Jacqueline Corricelli, 2021-03-05 Study only what you need to know-REA's Crash Course targets just what's on the test so you can make the most of your study time. Get practical test-taking tips-boost your score with advice from expert AP® teachers who know the test from the inside out. Build confidence with our online practice exam-balanced to include every type of question you can expect on the actual exam, so you'll be prepared on test day. Book jacket. |
| course outline for computer science: Think Python Allen B. Downey, 2015-12-02 If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, youâ??ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand objects, methods, and object-oriented programming Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design, data structures, and GUI-based programs through case studies |
Computer Science A Course Outline - IN.gov
Computer Science A (CSA) is designed to be a full-year (160-day) course implemented in the 12th grade. AP Computer Science A is an introductory college-level computer science course.
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The Computer Science curriculum is expected to provide environments to put into practice, the principles and techniques learnt during the course of implementation of academic
COMP 250 - Introduction to Computer Science - McGill …
This course introduces you to two core topics in computer science: data structures and algorithms. You will learn basic data structures for lists (arrays, linked lists, stacks, queues), …
Bachelor of Science, Computer Science program guide
The Bachelor of Science in Computer Science prepares students for a career in the high demand field of Computer Science. Upon program completion, students will apply their learned …
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Discuss their prior knowledge of computer science & coding in small groups and present to the class. Research a particular historically important moment for computing to share with the …
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Course Outline: Introduction to problem solving, a brief review of Von-Neumann architecture, Introduction to programming, role of compiler and linker, introduction to algorithms, basic data …
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concepts, principles, and practices in Computer Science for analyzing and solving real world problems to support industry as well as research and development organizations. The students …
CS1026a Computer Science Fundamentals I - uwo.ca
Computer Science CS1026: Computer Science Fundamentals I provides an introduction to the basic concepts of computer programming and program design. It is intended for students who …
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Computer Science Principles Course Outline - IN.gov
PLTW’s new Computer Science Principles course prepares students to excel on the AP Computer Science Principles exam and supports connections to College Board resources, including …
COMP 250 - Introduction to Computer Science - McGill …
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Road Map for Affiliated Colleges under Semester System BS …
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COMP1006:1406 B:E (Winter 2025) Introduction to Computer …
Course Description: A second course in programming emphasizing problem-solving and computational thinking in an object-oriented language. Topics include abstraction, mutable …
IP Addresses - CS50
and computer science overall. IP Addresses Devices on the Internet are assigned an IP address (which stands for Internet Protocol) to help …
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Scratch is a programming language designed to help introduce computer science prin- ciples while minimizing the amount of syntax you need to …
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The Routing Model - CS50
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