Azure Data Scientist Associate Certification Guide PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Azure Data Scientist Associate Certification Guide PDF full book. Access full book title Azure Data Scientist Associate Certification Guide by Andreas Botsikas. Download full books in PDF and EPUB format.
Author: Andreas Botsikas
Publisher: Packt Publishing Ltd
ISBN: 1800561261
Category : Computers
Languages : en
Pages : 448
Get Book
Book Description
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.
Author: Andreas Botsikas
Publisher: Packt Publishing Ltd
ISBN: 1800561261
Category : Computers
Languages : en
Pages : 448
Get Book
Book Description
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.
Author: Newton Alex
Publisher: Packt Publishing Ltd
ISBN: 1801812837
Category : Computers
Languages : en
Pages : 574
Get Book
Book Description
Become well-versed with data engineering concepts and exam objectives to achieve Azure Data Engineer Associate certification Key FeaturesUnderstand and apply data engineering concepts to real-world problems and prepare for the DP-203 certification examExplore the various Azure services for building end-to-end data solutionsGain a solid understanding of building secure and sustainable data solutions using Azure servicesBook Description Azure 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 learnGain intermediate-level knowledge of Azure the data infrastructureDesign and implement data lake solutions with batch and stream pipelinesIdentify the partition strategies available in Azure storage technologiesImplement different table geometries in Azure Synapse AnalyticsUse the transformations available in T-SQL, Spark, and Azure Data FactoryUse Azure Databricks or Synapse Spark to process data using NotebooksDesign security using RBAC, ACL, encryption, data masking, and moreMonitor and optimize data pipelines with debugging tipsWho 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.
Author: Julian Sharp
Publisher: Microsoft Press
ISBN: 0137358148
Category : Computers
Languages : en
Pages : 288
Get Book
Book Description
Prepare for Microsoft Exam AI-900 and help demonstrate your real-world knowledge of diverse machine learning (ML) and artificial intelligence (AI) workloads, and how they can be implemented with Azure AI. Designed for business stakeholders, new and existing IT professionals, consultants, and students, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure AI Fundamentals level. Focus on the expertise measured by these objectives: • Describe AI workloads and considerations • Describe fundamental principles of machine learning on Azure • Describe features of computer vision workloads on Azure • Describe features of Natural Language Processing (NLP) workloads on Azure • Describe features of conversational AI workloads on Azure This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you are a business user, stakeholder, technical professional, or student who wants to become familiar with Azure AI; requires no data science or software engineering experience. About the Exam Exam AI-900 focuses on knowledge needed to identify features of common AI workloads and guiding principles for responsible AI; identify common ML types; describe core ML concepts; identify core tasks in creating an ML solution; describe capabilities of no-code ML with Azure Machine Learning Studio; identify common types of computer vision solutions; identify Azure tools and services for computer vision tasks; identify features of common NLP workload scenarios; identify Azure tools and services for NLP workloads; and identify common use cases and Azure services for conversational Al. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure AI Fundamentals certification, demonstrating your knowledge of common ML and AI workloads and how to implement them on Azure. With this certification, you can move on to earn more advanced role-based certifications, including Microsoft Certified: Azure AI Engineer Associate or Azure Data Scientist Associate. See full details at: microsoft.com/learn
Author: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 140
Get Book
Book Description
Unlock the Power of Data with Azure Data Engineering! Are you ready to become a Microsoft Azure Data Engineer Associate and harness the transformative potential of data in the cloud? Look no further than the "Microsoft Certified Exam Guide - Azure Data Engineer Associate (DP-203)." This comprehensive book is your ultimate companion on the journey to mastering Azure data engineering and acing the DP-203 exam. In today's data-driven world, organizations depend on the efficient management, processing, and analysis of data to make critical decisions and drive innovation. Microsoft Azure provides a cutting-edge platform for data engineers to design and implement data solutions, and the demand for skilled professionals in this field is soaring. Whether you're an experienced data engineer or just starting your journey, this book equips you with the knowledge and skills needed to excel in Azure data engineering. Inside this book, you will discover: ✔ Comprehensive Coverage: A deep dive into all the key concepts, tools, and best practices required for designing, building, and maintaining data solutions on Azure. ✔ Real-World Scenarios: Practical examples and case studies that illustrate how Azure is used to solve complex data challenges, making learning engaging and relevant. ✔ Exam-Ready Preparation: Thorough coverage of DP-203 exam objectives, complete with practice questions and expert tips to ensure you're well-prepared for exam day. ✔ Proven Expertise: Authored by Azure data engineering professionals who hold the certification and have hands-on experience in developing data solutions, offering you invaluable insights and practical guidance. Whether you aspire to advance your career, validate your expertise, or simply become a proficient Azure Data Engineer, "Microsoft Certified Exam Guide - Azure Data Engineer Associate (DP-203)" is your trusted companion on this journey. Don't miss this opportunity to become a sought-after data engineering expert in a competitive job market. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Author: Benjamin Perkins
Publisher: John Wiley & Sons
ISBN: 1119885434
Category : Computers
Languages : en
Pages : 1077
Get Book
Book Description
Prepare for the Azure Data Engineering certification—and an exciting new career in analytics—with this must-have study aide In the MCA Microsoft Certified Associate Azure Data Engineer Study Guide: Exam DP-203, accomplished data engineer and tech educator Benjamin Perkins delivers a hands-on, practical guide to preparing for the challenging Azure Data Engineer certification and for a new career in an exciting and growing field of tech. In the book, you’ll explore all the objectives covered on the DP-203 exam while learning the job roles and responsibilities of a newly minted Azure data engineer. From integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions, you’ll get up to speed quickly and efficiently with Sybex’s easy-to-use study aids and tools. This Study Guide also offers: Career-ready advice for anyone hoping to ace their first data engineering job interview and excel in their first day in the field Indispensable tips and tricks to familiarize yourself with the DP-203 exam structure and help reduce test anxiety Complimentary access to Sybex’s expansive online study tools, accessible across multiple devices, and offering access to hundreds of bonus practice questions, electronic flashcards, and a searchable, digital glossary of key terms A one-of-a-kind study aid designed to help you get straight to the crucial material you need to succeed on the exam and on the job, the MCA Microsoft Certified Associate Azure Data Engineer Study Guide: Exam DP-203 belongs on the bookshelves of anyone hoping to increase their data analytics skills, advance their data engineering career with an in-demand certification, or hoping to make a career change into a popular new area of tech.
Author: Pierstefano Tucci
Publisher: Microsoft Press
ISBN: 9780136871798
Category : Computers
Languages : en
Pages : 240
Get Book
Book Description
Prepare for Microsoft Exam DP-100-and help demonstrate your real-world mastery of the various data science components of Microsoft Azure. Designed for IT professionals, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified Associate level. Focus on the expertise measured by these objectives: Set up an Azure Machine Learning workspace Run experiments and train models Optimize and manage models Deploy and consume models This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are a business user, IT professional, or student interested in cloud computing and technologies, including individuals planning to pursue more advanced Microsoft 365 certification About the Exam Exam DP-100 focuses on knowledge needed to apply scientific rigor and data exploration techniques to gain actionable insights and communicate results to stakeholders; use machine learning techniques to train, evaluate, and deploy models to build AI solutions that satisfy business objectives; use applications that involve natural language processing, speech, computer vision, and predictive analytics. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Scientist Associate credential, demonstrating that you understand how to implement and run machine learning workloads on Microsoft Azure; in particular, using Azure Machine Learning Service. See full details at: www.microsoft.com/learn
Author: GIACINTO. METTAPALLI PALMIERI (SURENDRA. ALEX, NEWTON.)
Publisher:
ISBN: 9781805124689
Category :
Languages : en
Pages : 0
Get Book
Book Description
Author: Cybellium Ltd
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 155
Get Book
Book Description
Become the Azure AI Expert of Tomorrow! Are you ready to embark on a journey into the world of artificial intelligence and machine learning within the Microsoft Azure ecosystem? Look no further than the "Microsoft Certified Exam Guide - Azure AI Engineer Associate (AI-102)." This comprehensive book is your ultimate companion on the path to mastering Azure AI and acing the AI-102 exam. In today's era of data-driven decision-making, AI and machine learning are the driving forces behind innovation and transformation. Microsoft Azure provides a robust platform for developing AI solutions, and organizations worldwide are seeking AI experts who can leverage its capabilities. Whether you're an AI enthusiast, a data scientist, or an IT professional, this book equips you with the knowledge and skills needed to excel in Azure AI. Inside this book, you will discover: ✔ Comprehensive Coverage: A deep dive into all the essential AI concepts, tools, and best practices for designing, implementing, and maintaining AI solutions on Azure. ✔ Real-World Scenarios: Practical examples and case studies that showcase how Azure AI is used to solve real business challenges, making learning both engaging and relevant. ✔ Exam-Ready Preparation: Thorough coverage of AI-102 exam objectives, complete with practice questions and expert tips to ensure you're well-prepared for exam day. ✔ Proven Expertise: Authored by Azure AI professionals who hold the certification and have hands-on experience in developing AI solutions, offering you invaluable insights and practical guidance. Whether you aspire to advance your career, validate your expertise, or simply become a proficient Azure AI Engineer, "Microsoft Certified Exam Guide - Azure AI Engineer Associate (AI-102)" is your trusted companion on this journey. Don't miss this opportunity to become a sought-after AI expert in a competitive job market. Prepare, practice, and succeed with the ultimate resource for AI-102 certification. Order your copy today and unlock a world of AI possibilities with Microsoft Azure! © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com
Author: Jack Hyman
Publisher: McGraw Hill Professional
ISBN: 1264268378
Category : Computers
Languages : en
Pages : 282
Get Book
Book Description
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
Author: Julien Simon
Publisher: Packt Publishing Ltd
ISBN: 1800203594
Category : Computers
Languages : en
Pages : 490
Get Book
Book Description
Quickly build and deploy machine learning models without managing infrastructure, and improve productivity using Amazon SageMaker’s capabilities such as Amazon SageMaker Studio, Autopilot, Experiments, Debugger, and Model Monitor Key FeaturesBuild, train, and deploy machine learning models quickly using Amazon SageMakerAnalyze, detect, and receive alerts relating to various business problems using machine learning algorithms and techniquesImprove productivity by training and fine-tuning machine learning models in productionBook Description Amazon SageMaker enables you to quickly build, train, and deploy machine learning (ML) models at scale, without managing any infrastructure. It helps you focus on the ML problem at hand and deploy high-quality models by removing the heavy lifting typically involved in each step of the ML process. This book is a comprehensive guide for data scientists and ML developers who want to learn the ins and outs of Amazon SageMaker. You’ll understand how to use various modules of SageMaker as a single toolset to solve the challenges faced in ML. As you progress, you’ll cover features such as AutoML, built-in algorithms and frameworks, and the option for writing your own code and algorithms to build ML models. Later, the book will show you how to integrate Amazon SageMaker with popular deep learning libraries such as TensorFlow and PyTorch to increase the capabilities of existing models. You’ll also learn to get the models to production faster with minimum effort and at a lower cost. Finally, you’ll explore how to use Amazon SageMaker Debugger to analyze, detect, and highlight problems to understand the current model state and improve model accuracy. By the end of this Amazon book, you’ll be able to use Amazon SageMaker on the full spectrum of ML workflows, from experimentation, training, and monitoring to scaling, deployment, and automation. What you will learnCreate and automate end-to-end machine learning workflows on Amazon Web Services (AWS)Become well-versed with data annotation and preparation techniquesUse AutoML features to build and train machine learning models with AutoPilotCreate models using built-in algorithms and frameworks and your own codeTrain computer vision and NLP models using real-world examplesCover training techniques for scaling, model optimization, model debugging, and cost optimizationAutomate deployment tasks in a variety of configurations using SDK and several automation toolsWho this book is for This book is for software engineers, machine learning developers, data scientists, and AWS users who are new to using Amazon SageMaker and want to build high-quality machine learning models without worrying about infrastructure. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. Some understanding of machine learning concepts and the Python programming language will also be beneficial.
