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Cloud computing - A Hands-On Approach is written as a textbook on cloud computing for educational programs at colleges and universities, and also for cloud service providers who may be interested in offering a broader perspective of cloud computing to accompany their own customer and developer training programs. The typical reader is expected to have completed a couple of courses in programming using traditional high-level languages at the college-level, and is either a senior or a beginning graduate student in one of the science, technology, engineering or mathematics (STEM) fields. We have tried to write a comprehensive book that transfers knowledge through an immersive \"hands on\" approach, where the reader is provided the necessary guidance and knowledge to develop working code for real-world cloud applications. Concurrent development of practical applications that accompanies traditional instructional material within the book further enhances the learning process, in our opinion.Organizationally, the book is organized into 3 main parts, comprising of a total of 13 chapters. Part I covers basic technologies that form the foundations of cloud computing. These include topics such as virtualization, load balancing, scalability & elasticity, deployment, replication. Real-world examples of cloud-based services and their characteristics are described.Part II introduces the reader to the programming aspects of cloud computing with a view towards rapid prototyping complex applications. We chose Python as the primary programming language for this book, and an introduction to Python is also included within the text to bring readers to a common level of expertise. We also describe packages and frameworks for Python that allows rapid prototyping of practical cloud applications. Reference architectures for different classes of cloud applications, including e-Commerce, Business-to-Business,Banking, Retail and Social Networking in the context of commonly used design methodologies are examined in detail. Other languages, besides Python, may also be easily used within the methodology outlined in this book.Part III introduces the reader to specialized aspects of cloud computing including cloud application benchmarking, multimedia cloud applications, cloud security and big data analytics. Case studies on the applications of the cloud in industry, healthcare, transportation systems, smart grids, and education are provided.Through generous use of hundreds of figures and tested code samples, we have attempted to provide a rigorous \"no hype\" guide to cloud computing. It is expected that diligent readers of this book can use these exercises to develop their own applications on cloud platforms, such as those from Amazon Web Services, Google Cloud, and Microsoft's Windows Azure. Review questions and exercises are provided at the end of each chapter so that the readers (students or instructors) can improve their understanding of the technologies conveyed. We adopted an informal approach to describing well-known concepts primarily because these topics are covered well in existing textbooks, and our focus instead is on getting the reader firmly on track to developing robust cloud applications as opposed to more theory. Table of Contents Click here to view Preface Click here to view Published December 9, 2013 Pages 454 Lecture SlidesDownload Recognition The book has been recognized by the ACM Computing Reviews' 19th Annual Best of Computing in 2014 list.
Abstract:Cloud computing instruction requires hands-on experience with a myriad of distributed computing services from a public cloud provider. Tracking the progress of the students, especially for online courses, requires one to automatically gather evidence and produce learning analytics in order to further determine the behavior and performance of students. With this aim, this paper describes the experience from an online course in cloud computing with Amazon Web Services on the creation of an open-source data processing tool to systematically obtain learning analytics related to the hands-on activities carried out throughout the course. These data, combined with the data obtained from the learning management system, have allowed the better characterization of the behavior of students in the course. Insights from a population of more than 420 online students through three academic years have been assessed, the dataset has been released for increased reproducibility. The results corroborate that course length has an impact on online students dropout. In addition, a gender analysis pointed out that there are no statistically significant differences in the final marks between genders, but women show an increased degree of commitment with the activities planned in the course.Keywords: learning analytics; cloud computing
A comprehensive, tech-focused program in AI and machine learning, the PGP-AIML course builds foundations in AI, machine learning, deep learning, and their respective applications in the business world. To enable candidates to independently build AI & ML solutions, the program uniquely combines a comprehensive curriculum (covering the most widely-used tools and techniques in the industry) with a hands-on learning approach. The program offers candidates the opportunity to apply their skills and knowledge in real-time every week through interactive mentor-led practice sessions, quizzes, case studies, and 10 hands-on projects. As they do so, they develop a nuanced understanding of data and build a strong body of work. A comprehensive career development support system further aids candidate targeting career transitions to AI & machine learning roles in industry.
Taking a business-focused approach towards emerging technologies in AI and machine learning, the PGP-AIFL equips managers and leaders with critical AI skills and enables them to understand their implications for business. The program is distinguished by its hands-on approach to teaching AI, through 5 hands-on projects and 1 capstone, without requiring candidates to code. The learning pedagogy incorporates numerous case studies, recorded lectures, mentor interactions, and webinars to teach the possibilities of AI and help candidates to translate AI solutions into business decisions.
Instead, this book is meant to help R users learn to use the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, lime, and others to effectively model and gain insight from your data. The book favors a hands-on approach, growing an intuitive understanding of machine learning through concrete examples and just a little bit of theory. While you can read this book without opening R, we highly recommend you experiment with the code examples provided throughout.
24) You have launched an RDS instance with MySQL database with default configuration for your file sharing application to store all the transactional information. Due to security compliance, your organization wants to encrypt all the databases and storage on the cloud. They approached you to perform this activity on your MySQL RDS database. How can you achieve this
Today, there are several examples of cloud computing applications used by both businesses and individuals. One type of cloud service would be streaming platforms for audio or video, where the actual media files are stored remotely. Another would be data storage platforms like Google Drive, Dropbox, OneDrive, or Box.\"}},{\"@type\": \"Question\",\"name\": \"What Are the Main Types of Cloud Computing\",\"acceptedAnswer\": {\"@type\": \"Answer\",\"text\": \"The main types of cloud computing services include Infrastructure-as-a-Service (IaaS), Platforms-as-a-Service (PaaS), and Software-as-a-Service (SaaS).IaaS provides IT infrastructure to end-users via the internet and is commonly associated with serverless computing.PaaS serves both software and hardware to end-users, who are generally software developers. PaaS allows the user to develop, run, and manage their own apps without having to build and maintain the infrastructure.SaaS is a software licensing model, which allows access to software on a subscription basis using external servers without having to download and install them locally.\"}},{\"@type\": \"Question\",\"name\": \"Is Cloud Computing Safe\",\"acceptedAnswer\": {\"@type\": \"Answer\",\"text\": \"Because software and data are stored remotely in cloud computing, data security and platform security are a big concern. Cloud security refers to the measures undertaken to protect digital assets and data stored on cloud-based services. Measures to protect this data include two-factor authorization (2FA), the use of VPNs, security tokens, data encryption, and firewall services, among others.\"}}]}]}] EducationGeneralDictionaryEconomicsCorporate FinanceRoth IRAStocksMutual FundsETFs401(k)Investing/TradingInvesting EssentialsFundamental AnalysisPortfolio ManagementTrading EssentialsTechnical AnalysisRisk ManagementNewsCompany NewsMarkets NewsCryptocurrency NewsPersonal Finance NewsEconomic NewsGovernment NewsSimulatorYour MoneyPersonal FinanceWealth ManagementBudgeting/SavingBankingCredit CardsHome OwnershipRetirement PlanningTaxesInsuranceReviews & RatingsBest Online BrokersBest Savings AccountsBest Home WarrantiesBest Credit CardsBest Personal LoansBest Student LoansBest Life InsuranceBest Auto InsuranceAdvisorsYour PracticePractice ManagementFinancial Advisor CareersInvestopedia 100Wealth ManagementPortfolio ConstructionFinancial PlanningAcademyPopular CoursesInvesting for BeginnersBecome a Day TraderTrading for BeginnersTechnical AnalysisCourses by TopicAll CoursesTrading CoursesInvesting CoursesFinancial Professional CoursesSubmitTable of ContentsExpandTable of ContentsWhat Is Cloud ComputingUnderstanding Cloud ComputingTypes of Cloud ServicesDeployment ModelsTypes of Cloud ComputingAdvantagesDisadvantagesThe World of BusinessCloud Computing FAQsLaws & RegulationsCybersecurityWhat is Cloud Computing Pros and Cons of Different Types of ServicesByJake FrankenfieldUpdated June 23, 2022Reviewed byJulius MansaFact checked byKirsten Rohrs Schmitt Investopedia / Joules Garcia 153554b96e
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