Exam DP-100: Azure Data Scientist Associate 48 Test Prep Questions

Exam DP-100: Azure Data Scientist Associate 48 Test Prep Questions

Author: Ger Arevalo

Publisher: Ger Arevalo

Published: 2019-08-29

Total Pages: 16

ISBN-13:

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This book is designed to be an ancillary to the classes, labs, and hands on practice that you have diligently worked on in preparing to obtain your DP-100: Azure Data Scientist Associate certification. I won’t bother talking about the benefits of certifications. This book tries to reinforce the knowledge that you have gained in your process of studying. It is meant as one of the end steps in your preparation for the DP-100 exam. This book is short, but It will give you a good gauge of your readiness. Learning can be seen in 4 stages: 1. Unconscious Incompetence 2. Conscious Incompetence 3. Conscious Competence 4. Unconscious Competence This book will assume the reader has already gone through the needed classes, labs, and practice. It is meant to take the reader from stage 2, Conscious Incompetence, to stage 3 Conscious Competence. At stage 3, you should be ready to take the exam. Only real-world scenarios and work experience will take you to stage 4, Unconscious Competence. Before we get started, we all have doubts when preparing to take an exam. What is your reason and purpose for taking this exam? Remember your reason and purpose when you have some doubts. Obstacle is the way. Control your mind, attitude, and you can control the situation. Persistence leads to confidence. Confidence erases doubts.


Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Author: Newton Alex

Publisher: Packt Publishing Ltd

Published: 2022-02-28

Total Pages: 574

ISBN-13: 1801812837

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Become well-versed with data engineering concepts and exam objectives to achieve Azure Data Engineer Associate certification Key Features Understand and apply data engineering concepts to real-world problems and prepare for the DP-203 certification exam Explore the various Azure services for building end-to-end data solutions Gain a solid understanding of building secure and sustainable data solutions using Azure services Book DescriptionAzure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.What you will learn Gain intermediate-level knowledge of Azure the data infrastructure Design and implement data lake solutions with batch and stream pipelines Identify the partition strategies available in Azure storage technologies Implement different table geometries in Azure Synapse Analytics Use the transformations available in T-SQL, Spark, and Azure Data Factory Use Azure Databricks or Synapse Spark to process data using Notebooks Design security using RBAC, ACL, encryption, data masking, and more Monitor and optimize data pipelines with debugging tips Who this book is for This book is for data engineers who want to take the DP-203: Azure Data Engineer Associate exam and are looking to gain in-depth knowledge of the Azure cloud stack. The book will also help engineers and product managers who are new to Azure or interviewing with companies working on Azure technologies, to get hands-on experience of Azure data technologies. A basic understanding of cloud technologies, extract, transform, and load (ETL), and databases will help you get the most out of this book.


Microsoft Certified Azure Fundamentals Study Guide

Microsoft Certified Azure Fundamentals Study Guide

Author: James Boyce

Publisher: John Wiley & Sons

Published: 2021-04-13

Total Pages: 256

ISBN-13: 1119771153

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Quickly preps technical and non-technical readers to pass the Microsoft AZ-900 certification exam Microsoft Certified Azure Fundamentals Study Guide: Exam AZ-900 is your complete resource for preparing for the AZ-900 exam. Microsoft Azure is a major component of Microsoft’s cloud computing model, enabling organizations to host their applications and related services in Microsoft’s data centers, eliminating the need for those organizations to purchase and manage their own computer hardware. In addition, serverless computing enables organizations to quickly and easily deploy data services without the need for servers, operating systems, and supporting systems. This book is targeted at anyone who is seeking AZ-900 certification or simply wants to understand the fundamentals of Microsoft Azure. Whatever your role in business or education, you will benefit from an understanding of Microsoft Azure fundamentals. Readers will also get one year of FREE access to Sybex’s superior online interactive learning environment and test bank, including hundreds of questions, a practice exam, electronic flashcards, and a glossary of key terms. This book will help you master the following topics covered in the AZ-900 certification exam: Cloud concepts Cloud types (Public, Private, Hybrid) Azure service types (IaaS, SaaS, PaaS) Core Azure services Security, compliance, privacy, and trust Azure pricing levels Legacy and modern lifecycles Growth in the cloud market continues to be very strong, and Microsoft is poised to see rapid and sustained growth in its cloud share. Written by a long-time Microsoft insider who helps customers move their workloads to and manage them in Azure on a daily basis, this book will help you break into the growing Azure space to take advantage of cloud technologies.


Microsoft Azure Essentials - Fundamentals of Azure

Microsoft Azure Essentials - Fundamentals of Azure

Author: Michael Collier

Publisher: Microsoft Press

Published: 2015-01-29

Total Pages: 400

ISBN-13: 0735697302

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Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. The first ebook in the series, Microsoft Azure Essentials: Fundamentals of Azure, introduces developers and IT professionals to the wide range of capabilities in Azure. The authors - both Microsoft MVPs in Azure - present both conceptual and how-to content for key areas, including: Azure Websites and Azure Cloud Services Azure Virtual Machines Azure Storage Azure Virtual Networks Databases Azure Active Directory Management tools Business scenarios Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the “Microsoft Azure Essentials” series.


Microsoft Certified Azure Fundamentals All-in-One Exam Guide (Exam AZ-900)

Microsoft Certified Azure Fundamentals All-in-One Exam Guide (Exam AZ-900)

Author: Jack Hyman

Publisher: McGraw Hill Professional

Published: 2021-08-27

Total Pages: 282

ISBN-13: 1264268378

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A highly effective, integrated self-study system for the Microsoft Azure Fundamentals exam Prepare for the current version of the Microsoft Azure Fundamentals exam using the detailed information contained in this test preparation guide. Written by a cloud computing expert and experienced author, the book contains accurate practice questions, step-by-step exercises, and special elements that aid in learning and reinforce retention. Microsoft Certified Azure Fundamentals All-in-One Exam Guide (Exam AZ-900) features in-depth coverage of every topic on the challenging exam. You will explore core Azure services, security, compliance, and trust. Fulfilling the promise of the All-in-One series, the guide serves as both a test preparation tool and an on-the-job reference for risk and compliance professionals. •100% coverage of all objectives for the Microsoft Azure Fundamentals exam •Contains hands-on exercises and practical use cases for Microsoft Azure •Online content includes practice exam software with 120 questions


Microsoft Azure Architect Technologies and Design Complete Study Guide

Microsoft Azure Architect Technologies and Design Complete Study Guide

Author: Benjamin Perkins

Publisher: John Wiley & Sons

Published: 2021-01-13

Total Pages: 768

ISBN-13: 1119559537

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Become a proficient Microsoft Azure solutions architect Azure certifications are critical to the millions of IT professionals Microsoft has certified as MCSE and MCSA in Windows Server in the last 20 years. All of these professionals need to certify in key Azure exams to stay current and advance in their careers. Exams AZ-303 and AZ-304 are the key solutions architect exams that experienced Windows professionals will find most useful at the intermediate and advanced points of their careers. Microsoft Azure Architect Technologies and Design Complete Study Guide Exams AZ-303 and AZ-304 covers the two critical Microsoft Azure exams that intermediate and advanced Microsoft IT professionals will need to show proficiency as their organizations move to the Azure cloud. Understand Azure Set up your Microsoft Cloud network Solve real-world problems Get the confidence to pass the exam By learning all of these things plus using the Study Guide review questions and practice exams, the reader will be ready to take the exam and perform the job with confidence.


The Data Science Design Manual

The Data Science Design Manual

Author: Steven S. Skiena

Publisher: Springer

Published: 2017-07-01

Total Pages: 456

ISBN-13: 3319554441

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This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)


AWS Certified Data Analytics Study Guide with Online Labs

AWS Certified Data Analytics Study Guide with Online Labs

Author: Asif Abbasi

Publisher: John Wiley & Sons

Published: 2021-04-13

Total Pages: 416

ISBN-13: 1119819458

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Virtual, hands-on learning labs allow you to apply your technical skills in realistic environments. So Sybex has bundled AWS labs from XtremeLabs with our popular AWS Certified Data Analytics Study Guide to give you the same experience working in these labs as you prepare for the Certified Data Analytics Exam that you would face in a real-life application. These labs in addition to the book are a proven way to prepare for the certification and for work as an AWS Data Analyst. AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam is intended for individuals who perform in a data analytics-focused role. This UPDATED exam validates an examinee's comprehensive understanding of using AWS services to design, build, secure, and maintain analytics solutions that provide insight from data. It assesses an examinee's ability to define AWS data analytics services and understand how they integrate with each other; and explain how AWS data analytics services fit in the data lifecycle of collection, storage, processing, and visualization. The book focuses on the following domains: • Collection • Storage and Data Management • Processing • Analysis and Visualization • Data Security This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS cloud. AWS is the frontrunner in cloud computing products and services, and the AWS Certified Data Analytics Study Guide: Specialty exam will get you fully prepared through expert content, and real-world knowledge, key exam essentials, chapter review questions, and much more. Written by an AWS subject-matter expert, this study guide covers exam concepts, and provides key review on exam topics. Readers will also have access to Sybex's superior online interactive learning environment and test bank, including chapter tests, practice exams, a glossary of key terms, and electronic flashcards. And included with this version of the book, XtremeLabs virtual labs that run from your browser. The registration code is included with the book and gives you 6 months of unlimited access to XtremeLabs AWS Certified Data Analytics Labs with 3 unique lab modules based on the book.


Azure Data Scientist Associate Certification Guide

Azure Data Scientist Associate Certification Guide

Author: Andreas Botsikas

Publisher: Packt Publishing Ltd

Published: 2021-12-03

Total Pages: 448

ISBN-13: 1800561261

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Develop the skills you need to run machine learning workloads in Azure and pass the DP-100 exam with ease Key FeaturesCreate end-to-end machine learning training pipelines, with or without codeTrack experiment progress using the cloud-based MLflow-compatible process of Azure ML servicesOperationalize your machine learning models by creating batch and real-time endpointsBook Description The Azure Data Scientist Associate Certification Guide helps you acquire practical knowledge for machine learning experimentation on Azure. It covers everything you need to pass the DP-100 exam and become a certified Azure Data Scientist Associate. Starting with an introduction to data science, you'll learn the terminology that will be used throughout the book and then move on to the Azure Machine Learning (Azure ML) workspace. You'll discover the studio interface and manage various components, such as data stores and compute clusters. Next, the book focuses on no-code and low-code experimentation, and shows you how to use the Automated ML wizard to locate and deploy optimal models for your dataset. You'll also learn how to run end-to-end data science experiments using the designer provided in Azure ML Studio. You'll then explore the Azure ML Software Development Kit (SDK) for Python and advance to creating experiments and publishing models using code. The book also guides you in optimizing your model's hyperparameters using Hyperdrive before demonstrating how to use responsible AI tools to interpret and debug your models. Once you have a trained model, you'll learn to operationalize it for batch or real-time inferences and monitor it in production. By the end of this Azure certification study guide, you'll have gained the knowledge and the practical skills required to pass the DP-100 exam. What you will learnCreate a working environment for data science workloads on AzureRun data experiments using Azure Machine Learning servicesCreate training and inference pipelines using the designer or codeDiscover the best model for your dataset using Automated MLUse hyperparameter tuning to optimize trained modelsDeploy, use, and monitor models in productionInterpret the predictions of a trained modelWho this book is for This book is for developers who want to infuse their applications with AI capabilities and data scientists looking to scale their machine learning experiments in the Azure cloud. Basic knowledge of Python is needed to follow the code samples used in the book. Some experience in training machine learning models in Python using common frameworks like scikit-learn will help you understand the content more easily.


Model-Based Machine Learning

Model-Based Machine Learning

Author: John Winn

Publisher: CRC Press

Published: 2023-11-30

Total Pages: 469

ISBN-13: 1498756824

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Today, machine learning is being applied to a growing variety of problems in a bewildering variety of domains. A fundamental challenge when using machine learning is connecting the abstract mathematics of a machine learning technique to a concrete, real world problem. This book tackles this challenge through model-based machine learning which focuses on understanding the assumptions encoded in a machine learning system and their corresponding impact on the behaviour of the system. The key ideas of model-based machine learning are introduced through a series of case studies involving real-world applications. Case studies play a central role because it is only in the context of applications that it makes sense to discuss modelling assumptions. Each chapter introduces one case study and works through step-by-step to solve it using a model-based approach. The aim is not just to explain machine learning methods, but also showcase how to create, debug, and evolve them to solve a problem. Features: Explores the assumptions being made by machine learning systems and the effect these assumptions have when the system is applied to concrete problems. Explains machine learning concepts as they arise in real-world case studies. Shows how to diagnose, understand and address problems with machine learning systems. Full source code available, allowing models and results to be reproduced and explored. Includes optional deep-dive sections with more mathematical details on inference algorithms for the interested reader.