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| certified data science practitioner: DAMA-DMBOK Dama International, 2017 Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment. |
| certified data science practitioner: Practitioner’s Guide to Data Science Nasir Ali Mirza, 2022-01-17 Covers Data Science concepts, processes, and the real-world hands-on use cases. KEY FEATURES ● Covers the journey from a basic programmer to an effective Data Science developer. ● Applied use of Data Science native processes like CRISP-DM and Microsoft TDSP. ● Implementation of MLOps using Microsoft Azure DevOps. DESCRIPTION How is the Data Science project to be implemented? has never been more conceptually sounding, thanks to the work presented in this book. This book provides an in-depth look at the current state of the world's data and how Data Science plays a pivotal role in everything we do. This book explains and implements the entire Data Science lifecycle using well-known data science processes like CRISP-DM and Microsoft TDSP. The book explains the significance of these processes in connection with the high failure rate of Data Science projects. The book helps build a solid foundation in Data Science concepts and related frameworks. It teaches how to implement real-world use cases using data from the HMDA dataset. It explains Azure ML Service architecture, its capabilities, and implementation to the DS team, who will then be prepared to implement MLOps. The book also explains how to use Azure DevOps to make the process repeatable while we're at it. By the end of this book, you will learn strong Python coding skills, gain a firm grasp of concepts such as feature engineering, create insightful visualizations and become acquainted with techniques for building machine learning models. WHAT YOU WILL LEARN ● Organize Data Science projects using CRISP-DM and Microsoft TDSP. ● Learn to acquire and explore data using Python visualizations. ● Get well versed with the implementation of data pre-processing and Feature Engineering. ● Understand algorithm selection, model development, and model evaluation. ● Hands-on with Azure ML Service, its architecture, and capabilities. ● Learn to use Azure ML SDK and MLOps for implementing real-world use cases. WHO THIS BOOK IS FOR This book is intended for programmers who wish to pursue AI/ML development and build a solid conceptual foundation and familiarity with related processes and frameworks. Additionally, this book is an excellent resource for Software Architects and Managers involved in the design and delivery of Data Science-based solutions. TABLE OF CONTENTS 1. Data Science for Business 2. Data Science Project Methodologies and Team Processes 3. Business Understanding and Its Data Landscape 4. Acquire, Explore, and Analyze Data 5. Pre-processing and Preparing Data 6. Developing a Machine Learning Model 7. Lap Around Azure ML Service 8. Deploying and Managing Models |
| certified data science practitioner: NSCA's Essentials of Sport Science NSCA -National Strength & Conditioning Association, Duncan French, Lorena Torres Ronda, 2021-02-19 NSCA's Essentials of Sport Science provides the most contemporary and comprehensive overview of the field of sport science and the role of the sport scientist. It is a primary preparation resource for the Certified Performance and Sport Scientist (CPSS) certification exam. |
| certified data science practitioner: Brain-Inspired Computing Katrin Amunts, Lucio Grandinetti, Thomas Lippert, Nicolai Petkov, 2021-07-20 This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures. |
| certified data science practitioner: Data Science at the Command Line Jeroen Janssens, 2014-09-25 This hands-on guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You’ll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data. To get you started—whether you’re on Windows, OS X, or Linux—author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools. Discover why the command line is an agile, scalable, and extensible technology. Even if you’re already comfortable processing data with, say, Python or R, you’ll greatly improve your data science workflow by also leveraging the power of the command line. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on plain text, CSV, HTML/XML, and JSON Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow using Drake Create reusable tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines using GNU Parallel Model data with dimensionality reduction, clustering, regression, and classification algorithms |
| certified data science practitioner: Acute Care Nurse Practitioner Certification Study Question Book Sally K. Miller, 2011 Review Guides/Certification Prep/Pocket Guides |
| certified data science practitioner: Family Nurse Practitioner Certification Intensive Review Maria T. Codina Leik, 2013-08-12 Print+CourseSmart |
| certified data science practitioner: Data Science and Big Data Analytics EMC Education Services, 2014-12-19 Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today! |
| certified data science practitioner: CompTIA Data+ Study Guide Mike Chapple, Sharif Nijim, 2022-03-18 Build a solid foundation in data analysis skills and pursue a coveted Data+ certification with this intuitive study guide CompTIA Data+ Study Guide: Exam DA0-001 delivers easily accessible and actionable instruction for achieving data analysis competencies required for the job and on the CompTIA Data+ certification exam. You'll learn to collect, analyze, and report on various types of commonly used data, transforming raw data into usable information for stakeholders and decision makers. With comprehensive coverage of data concepts and environments, data mining, data analysis, visualization, and data governance, quality, and controls, this Study Guide offers: All the information necessary to succeed on the exam for a widely accepted, entry-level credential that unlocks lucrative new data analytics and data science career opportunities 100% coverage of objectives for the NEW CompTIA Data+ exam Access to the Sybex online learning resources, with review questions, full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms Ideal for anyone seeking a new career in data analysis, to improve their current data science skills, or hoping to achieve the coveted CompTIA Data+ certification credential, CompTIA Data+ Study Guide: Exam DA0-001 provides an invaluable head start to beginning or accelerating a career as an in-demand data analyst. |
| certified data science practitioner: Pediatric Nurse Practitioner Certification Review Guide JoAnne Silbert-Flagg, Elizabeth Sloand, 2010-08-15 Rev. ed. of: Pediatric nurse practitioner certification review guide / editors, Virginia Layng Millonig, Caryl E. Mobley. 4th ed. c2004. |
| certified data science practitioner: Data Science For Cyber-security Nicholas A Heard, Niall M Adams, Patrick Rubin-delanchy, Mellisa Turcotte, 2018-09-26 Cyber-security is a matter of rapidly growing importance in industry and government. This book provides insight into a range of data science techniques for addressing these pressing concerns.The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences. Networks of connected devices, such as enterprise computer networks or the wider so-called Internet of Things, are all vulnerable to misuse and attack, and data science methods offer the promise to detect such behaviours from the vast collections of cyber traffic data sources that can be obtained. In many cases, this is achieved through anomaly detection of unusual behaviour against understood statistical models of normality.This volume presents contributed papers from an international conference of the same name held at Imperial College. Experts from the field have provided their latest discoveries and review state of the art technologies. |
| certified data science practitioner: Psychiatric-Mental Health Nurse (PMH-BCTM) Certification Review Raymond Zakhari, DNP, EdM, ANP-BC, FNP-BC, PMHNP-BC, 2021-12-02 Psychiatric-Mental Health Nursing (PMH-BC™) Certification Review is designed to help you prepare for the American Nurses Credentialing Center (ANCC) board certification exam. This comprehensive study aid begins with an overview of the exam, scope and standards of practice, and fundamental theories. It examines topics such as therapeutic treatment and management, patient education, cultural competence, communication, health promotion, and crisis management. A wide range of psychiatric disorders, as organized in the DSM-5, are systematically reviewed in a templated approach that takes the reader through the nursing process step by step. Each chapter covers everything you need to know to pass the exam and includes end-of-chapter questions to check your knowledge. The review concludes with a full-length practice test to get you ready for exam day. With over 300 practice questions and detailed review content and answer rationales, this study aid empowers you with the tools and materials to study your way and the confidence to pass the first time, guaranteed! Know that you're ready. Know that you'll pass with Springer Publishing Exam Prep. Key Features Reflects the latest ANCC exam blueprint Provides a comprehensive yet concise review of essential knowledge for the exam Includes test-taking strategies and tips, scope of practice, and fundamental theories Covers the most commonly encountered psychiatric disorders, as organized in the DSM-5 Includes end-of-chapter Q&A and a full practice test with detailed rationales Boosts your confidence with a 100% pass guarantee PMH-BC™ is a registered service mark of American Nurses Credentialing Center (ANCC). ANCC does not sponsor or endorse this resource, nor does it have a proprietary relationship with Springer Publishing. |
| certified data science practitioner: (ISC)2 SSCP Systems Security Certified Practitioner Official Study Guide Mike Wills, 2019-04-24 The only SSCP study guide officially approved by (ISC)2 The (ISC)2 Systems Security Certified Practitioner (SSCP) certification is a well-known vendor-neutral global IT security certification. The SSCP is designed to show that holders have the technical skills to implement, monitor, and administer IT infrastructure using information security policies and procedures. This comprehensive Official Study Guide—the only study guide officially approved by (ISC)2—covers all objectives of the seven SSCP domains. Access Controls Security Operations and Administration Risk Identification, Monitoring, and Analysis Incident Response and Recovery Cryptography Network and Communications Security Systems and Application Security If you’re an information security professional or student of cybersecurity looking to tackle one or more of the seven domains of the SSCP, this guide gets you prepared to pass the exam and enter the information security workforce with confidence. |
| certified data science practitioner: Azure Data Scientist Associate Certification Guide Andreas Botsikas, Michael Hlobil, 2021-12-03 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. |
| certified data science practitioner: AWS Certified Data Analytics Study Guide Asif Abbasi, 2020-11-20 Move your career forward with AWS certification! Prepare for the AWS Certified Data Analytics Specialty Exam with this thorough study guide This comprehensive study guide will help assess your technical skills and prepare for the updated AWS Certified Data Analytics exam. Earning this AWS certification will confirm your expertise in designing and implementing AWS services to derive value from data. The AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam is designed for business analysts and IT professionals who perform complex Big Data analyses. This AWS Specialty Exam guide gets you ready for certification testing with expert content, real-world knowledge, key exam concepts, and topic reviews. Gain confidence by studying the subject areas and working through the practice questions. Big data concepts covered in the guide include: Collection Storage Processing Analysis Visualization Data security AWS certifications allow professionals to demonstrate skills related to leading Amazon Web Services technology. The AWS Certified Data Analytics Specialty (DAS-C01) Exam specifically evaluates your ability to design and maintain Big Data, leverage tools to automate data analysis, and implement AWS Big Data services according to architectural best practices. An exam study guide can help you feel more prepared about taking an AWS certification test and advancing your professional career. In addition to the guide’s content, you’ll have access to an online learning environment and test bank that offers practice exams, a glossary, and electronic flashcards. |
| certified data science practitioner: Learn By Examples - A Quick Guide To Data Science With Python Eric M. H. Goh , This book aim to equip the reader with Python Programming and Data Science basics. There will be many examples and explanations that are straight to the point. You will be walked through data mining process from data preparation to data analysis (descriptive statistics) and data visualization to prediction modeling (machine learning) and deployment using Python. Content Covered: IntroductionGetting Started (Installing WinPython, IDE, ...)Language Essentials (variables, list, data types manipulations, ...)Language Essentials II (conditional statements, loops, ...)Object Essentials (Modules, Class and Objects, ...)Data Mining with Python (Pandas, ScikitLearn, ...) We will be using opensource tools and IDE, hence, you don't have to worry about buying any softwares. The book is designed for non-programmers only. It will gives you a head start into python programming, with a touch on data mining. This book has been taught at Udemy and EMHAcademy.com. Use the following Coupon to get the Udemy Course at $11.99: https://www.udemy.com/fundamentals-of-python-for-data-mining/?couponCode=EBOOKSPECIAL ISBN: 978-163535299-3 |
| certified data science practitioner: Practical MLOps Noah Gift, Alfredo Deza, 2021-09-14 Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start. You'll discover how to: Apply DevOps best practices to machine learning Build production machine learning systems and maintain them Monitor, instrument, load-test, and operationalize machine learning systems Choose the correct MLOps tools for a given machine learning task Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware |
| certified data science practitioner: Official Google Cloud Certified Professional Data Engineer Study Guide Dan Sullivan, 2020-05-11 The proven Study Guide that prepares you for this new Google Cloud exam The Google Cloud Certified Professional Data Engineer Study Guide, provides everything you need to prepare for this important exam and master the skills necessary to land that coveted Google Cloud Professional Data Engineer certification. Beginning with a pre-book assessment quiz to evaluate what you know before you begin, each chapter features exam objectives and review questions, plus the online learning environment includes additional complete practice tests. Written by Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Google Cloud Certified Professional Data Engineer Study Guide is your ace in the hole for deploying and managing analytics and machine learning applications. Build and operationalize storage systems, pipelines, and compute infrastructure Understand machine learning models and learn how to select pre-built models Monitor and troubleshoot machine learning models Design analytics and machine learning applications that are secure, scalable, and highly available. This exam guide is designed to help you develop an in depth understanding of data engineering and machine learning on Google Cloud Platform. |
| certified data science practitioner: Family Nurse Practitioner Certification Intensive Review, Fourth Edition Maria Codina Leik, MSN, ARNP, FNP-C, AGPCNP-BC, 2021-01-15 If you are studying for the family nurse practitioner certification exam, the highly acclaimed Family Nurse Practitioner Certification Intensive Review is a must-have resource. Lauded for its concise, well-organized format, this fourth edition has been significantly revised and updated to feature key information about the new AANPCB and ANCC certification exams, all new end-of-chapter review questions, and new full-color images. The fourth edition also features four practice tests with hundreds of new questions and rationales—800 questions in total. Extensive test-taking techniques and question dissection and analysis chapters help you identify the best clues during the problem-solving process so that you can strategically master the certification exam. Designed to help FNP candidates boost their confidence through intensive review and high-quality questions, the fourth edition continues to provide succinct, precisely targeted “need-to-know” details of diseases and classic presentations you can expect to see in practice in patients across the life span. Organized by body system, chapters are consistently formatted to include Danger Signals, Normal Findings, Lab Findings, Benign Variants, and Disease Review topics. Each chapter features valuable Exam Tips and Clinical Pearls that highlight key considerations and information likely to be encountered on the exam, ideal for a last-minute refresher before test day. Ensure success by making this essential resource—praised by thousands for helping them pass their certification—a key part of your exam prep study regimen. Key Features: Includes updated information reflecting the new AANPCB and ANCC certification exams Introduces new end-of-chapter review questions to help you assess knowledge application and retention Features four practice tests with hundreds of new questions and rationales Provides a succinct and highly targeted review of diseases commonly seen in primary care, updated clinical information, all new color photos, and Exam Tips and Clinical Pearls to highlight key exam content Outlines Danger Signals, Normal Findings, Lab Findings, and Benign Variants in physical assessment of each body system Delineates strategic question-dissection techniques to simplify the problem-solving process Offers an intensive pharmacology review and review of professional issues—ethical guidelines, professional roles, reimbursement, research, evidence-based medicine and epidemiology, and cultural considerations |
| certified data science practitioner: Data Science on AWS Chris Fregly, Antje Barth, 2021-04-07 With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more |
| certified data science practitioner: Adult and Family Nurse Practitioner Certification Practice Questions Amelie Hollier, 2009 |
| certified data science practitioner: Fundamentals of Clinical Data Science Pieter Kubben, Michel Dumontier, Andre Dekker, 2018-12-21 This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience. |
| certified data science practitioner: Mathematics for Machine Learning Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong, 2020-04-23 The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site. |
| certified data science practitioner: Neonatal Nurse Practitioner Certification Intensive Review Amy R. Koehn, PhD, NNP-BC, 2019-12-13 The definitive certification review for exam success! Written by leading APRN neonatal educators and clinicians, this authoritative study guide delivers all the tools neonatal nurse practitioners need to pass the National Certification Corporation (NCC) certification exam and the Continuing Competency Assessment (CCA). User friendly and concise, this review’s content mirrors that of the actual exam and is structured in accordance with the most updated test plan blueprint. This resource’s numerous exam-style questions and answers with rationales included in each chapter help readers uncover gaps in their knowledge. This review synthesizes the knowledge required to pass the exam, saving the reader time and effort by omitting extraneous material. In addition to spotlighting essential content throughout the text, recommended references provide the reader with the option to seek out additional information as needed. Additional benefits include important information about the exam along with savvy study and test-taking tips. This review will ensure exam success for both new NNPs and those who are taking the CCA exam. KEY FEATURES Mirrors the format of the certification exam Concise outline format for easy access to essential content Written by leading NNP educators and clinicians Includes valuable study and test-taking tips Exam-style questions and answers with explanatory rationales Includes more than double the amount of questions on the exam, including a 175-question simulated practice exam Purchase includes digital access for use on most mobile devices or computers |
| certified data science practitioner: Pragmatic AI Noah Gift, 2018-07-12 Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| certified data science practitioner: Introducing MLOps Mark Treveil, Nicolas Omont, Clément Stenac, Kenji Lefevre, Du Phan, Joachim Zentici, Adrien Lavoillotte, Makoto Miyazaki, Lynn Heidmann, 2020-11-30 More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized |
| certified data science practitioner: Engineering MLOps Emmanuel Raj, 2021-04-19 Get up and running with machine learning life cycle management and implement MLOps in your organization Key FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed modelsPerform CI/CD to automate new implementations in ML pipelinesBook Description Engineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production. The book begins by familiarizing you with the MLOps workflow so you can start writing programs to train ML models. Then you'll then move on to explore options for serializing and packaging ML models post-training to deploy them to facilitate machine learning inference, model interoperability, and end-to-end model traceability. You'll learn how to build ML pipelines, continuous integration and continuous delivery (CI/CD) pipelines, and monitor pipelines to systematically build, deploy, monitor, and govern ML solutions for businesses and industries. Finally, you'll apply the knowledge you've gained to build real-world projects. By the end of this ML book, you'll have a 360-degree view of MLOps and be ready to implement MLOps in your organization. What you will learnFormulate data governance strategies and pipelines for ML training and deploymentGet to grips with implementing ML pipelines, CI/CD pipelines, and ML monitoring pipelinesDesign a robust and scalable microservice and API for test and production environmentsCurate your custom CD processes for related use cases and organizationsMonitor ML models, including monitoring data drift, model drift, and application performanceBuild and maintain automated ML systemsWho this book is for This MLOps book is for data scientists, software engineers, DevOps engineers, machine learning engineers, and business and technology leaders who want to build, deploy, and maintain ML systems in production using MLOps principles and techniques. Basic knowledge of machine learning is necessary to get started with this book. |
| certified data science practitioner: Midwifery and Women's Health Nurse Practitioner Certification Review Guide Beth M. Kelsey, Jamille Nagtalon-Ramos, 2014-09 Midwifery & Women's Health Nurse Practitioner Certification Review Guide, Third Edition is a comprehensive review designed to help midwives and women's health nurse practitioners prepare for certification exams. Based on the American Midwifery Certification Board (AMCB) and the National Certification Corporation (NCC) test blueprints, it contains nearly 1,000 questions and comprehensive rationales representing those found on the exams. Completely updated and revised with the most current evidence and practice standards, the new edition incorporates expanded content on pharmacology, pathophysiology, and diagnostic tools. Included with each new print book is an online Access Code for Navigate TestPrep, a dynamic and fully hosted online assessment tool offering hundreds of bonus questions in addition to those in the book, detailed rationales, and reporting. |
| certified data science practitioner: Scala and Spark for Big Data Analytics Md. Rezaul Karim, Sridhar Alla, 2017-07-25 Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book Learn Scala's sophisticated type system that combines Functional Programming and object-oriented concepts Work on a wide array of applications, from simple batch jobs to stream processing and machine learning Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn Understand object-oriented & functional programming concepts of Scala In-depth understanding of Scala collection APIs Work with RDD and DataFrame to learn Spark's core abstractions Analysing structured and unstructured data using SparkSQL and GraphX Scalable and fault-tolerant streaming application development using Spark structured streaming Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML Build clustering models to cluster a vast amount of data Understand tuning, debugging, and monitoring Spark applications Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist. |
| certified data science practitioner: Lippincott Certification Review: Pediatric Acute Care Nurse Practitioner Andrea M. Kline, Catherine Haut, 2015-08-10 Lippincott Certification Review: Pediatric Acute Care Nurse Practitioner is the ideal companion while preparing for the Acute Care CPNP® exam administered by the Pediatric Nursing Certification Review Board, or for anyone who seeks to perform at a higher level of practice for children who are acutely, chronically, and critically ill. Organized in a simple, bulleted format, this invaluable resource includes multiple choice self-assessment questions with rationales at the end of every chapter, plus two self-assessment exams with rationales – totaling more than 750 questions. Content focuses on the diagnosis and management of pediatric acute care problems typically treated in the emergency department or an inpatient setting. |
| certified data science practitioner: Guide to Business Data Analytics Iiba, 2020-08-07 The Guide to Business Data Analytics provides a foundational understanding of business data analytics concepts and includes how to develop a framework; key techniques and application; how to identify, communicate and integrate results; and more. This guide acts as a reference for the practice of business data analytics and is a companion resource for the Certification in Business Data Analytics (IIBA(R)- CBDA). Explore more information about the Certification in Business Data Analytics at IIBA.org/CBDA. About International Institute of Business Analysis International Institute of Business Analysis(TM) (IIBA(R)) is a professional association dedicated to supporting business analysis professionals deliver better business outcomes. IIBA connects almost 30,000 Members, over 100 Chapters, and more than 500 training, academic, and corporate partners around the world. As the global voice of the business analysis community, IIBA supports recognition of the profession, networking and community engagement, standards and resource development, and comprehensive certification programs. IIBA Publications IIBA publications offer a wide variety of knowledge and insights into the profession and practice of business analysis for the entire business community. Standards such as A Guide to the Business Analysis Body of Knowledge(R) (BABOK(R) Guide), the Agile Extension to the BABOK(R) Guide, and the Global Business Analysis Core Standard represent the most commonly accepted practices of business analysis around the globe. IIBA's reports, research, whitepapers, and studies provide guidance and best practices information to address the practice of business analysis beyond the global standards and explore new and evolving areas of practice to deliver better business outcomes. Learn more at iiba.org. |
| certified data science practitioner: (ISC)2 SSCP Systems Security Certified Practitioner Official Practice Tests Mike Chapple, David Seidl, 2019-01-14 Smarter, faster prep for the SSCP exam The (ISC)² SSCP Official Practice Tests is the only (ISC)²-endorsed set of practice questions for the Systems Security Certified Practitioner (SSCP). This book's first seven chapters cover each of the seven domains on the SSCP exam with sixty or more questions per domain, so you can focus your study efforts exactly where you need more review. When you feel well prepared, use the two complete practice exams from Sybex's online interactive learning environment as time trials to assess your readiness to take the exam. Coverage of all exam objectives, including: Access Controls Security Operations and Administration Risk Identification, Monitoring, and Analysis Incident Response and Recovery Cryptography Network and Communications Security Systems and Application Security SSCP certification demonstrates you have the advanced technical skills and knowledge to implement, monitor and administer IT infrastructure using security best practices, policies and procedures. It's ideal for students pursuing cybersecurity degrees as well as those in the field looking to take their careers to the next level. |
| certified data science practitioner: AWS Certified Cloud Practitioner Study Guide Ben Piper, David Clinton, 2019-06-10 Set yourself apart by becoming an AWS Certified Cloud Practitioner Take the next step in your career by expanding and validating your skills on the Amazon Web Services (AWS) Cloud. The AWS Certified Cloud Practitioner Study Guide: Exam CLF-C01 provides a solid introduction to this industry-leading technology, relied upon by thousands of businesses across the globe, as well as the resources you need to prove your knowledge in the AWS Certification Exam. This guide offers complete and thorough treatment of all topics included in the exam, beginning with a discussion of what the AWS cloud is and its basic global infrastructure and architectural principles. Other chapters dive into the technical, exploring core characteristics of deploying and operating in the AWS Cloud Platform, as well as basic security and compliance aspects and the shared security model. In addition, the text identifies sources of documentation or technical assistance, such as white papers or support tickets. To complete their coverage, the authors discuss the AWS Cloud value proposition and define billing, account management, and pricing models. This includes describing the key services AWS can provide and their common use cases (e.g., compute, analytics, etc.). Distinguish yourself as an expert by obtaining a highly desirable certification in a widely used platform Hone your skills and gain new insights on AWS whether you work in a technical, managerial, sales, purchasing, or financial field Fully prepare for this new exam using expert content and real-world knowledge, key exam essentials, chapter review questions, and other textual resources Benefit from 1 year free access to the Sybex online interactive learning environment and test bank, including chapter tests, practice exams, key term glossary, and electronic flashcards, all supported by Wiley's support agents who are available 24x7 via email or live chat to assist with access and login questions The AWS Certified Cloud Practitioner Study Guide is essential reading for any professional in IT or other fields that work directly with AWS, soon-to-be graduates studying in those areas, or anyone hoping to prove themselves as an AWS Certified Cloud Practitioner. |
| certified data science practitioner: Human + Machine Paul R. Daugherty, H. James Wilson, 2018-03-20 AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that think in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a leader’s guide with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence. |
| certified data science practitioner: ADKAR Jeff Hiatt, 2006 In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change. |
| certified data science practitioner: Rise of the Data Cloud Frank Slootman, Steve Hamm, 2020-12-18 The rise of the Data Cloud is ushering in a new era of computing. The world’s digital data is mass migrating to the cloud, where it can be more effectively integrated, managed, and mobilized. The data cloud eliminates data siloes and enables data sharing with business partners, capitalizing on data network effects. It democratizes data analytics, making the most sophisticated data science tools accessible to organizations of all sizes. Data exchanges enable businesses to discover, explore, and easily purchase or sell data—opening up new revenue streams. Business leaders have long dreamed of data driving their organizations. Now, thanks to the Data Cloud, nothing stands in their way. |
| certified data science practitioner: Cybersecurity Data Science Scott Mongeau, Andrzej Hajdasinski, 2021-10-01 This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography. |
| certified data science practitioner: Effective Data Storytelling Brent Dykes, 2019-12-10 Master the art and science of data storytelling—with frameworks and techniques to help you craft compelling stories with data. The ability to effectively communicate with data is no longer a luxury in today’s economy; it is a necessity. Transforming data into visual communication is only one part of the picture. It is equally important to engage your audience with a narrative—to tell a story with the numbers. Effective Data Storytelling will teach you the essential skills necessary to communicate your insights through persuasive and memorable data stories. Narratives are more powerful than raw statistics, more enduring than pretty charts. When done correctly, data stories can influence decisions and drive change. Most other books focus only on data visualization while neglecting the powerful narrative and psychological aspects of telling stories with data. Author Brent Dykes shows you how to take the three central elements of data storytelling—data, narrative, and visuals—and combine them for maximum effectiveness. Taking a comprehensive look at all the elements of data storytelling, this unique book will enable you to: Transform your insights and data visualizations into appealing, impactful data stories Learn the fundamental elements of a data story and key audience drivers Understand the differences between how the brain processes facts and narrative Structure your findings as a data narrative, using a four-step storyboarding process Incorporate the seven essential principles of better visual storytelling into your work Avoid common data storytelling mistakes by learning from historical and modern examples Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals is a must-have resource for anyone who communicates regularly with data, including business professionals, analysts, marketers, salespeople, financial managers, and educators. |
| certified data science practitioner: Assessment and Diagnosis Review for Advanced Practice Nursing Certification Exams Alice M. Teall, DNP, APRN-CNP, FAANP, Kate Sustersic Gawlik, DNP, APRN-CNP, FAANP, Bernadette Mazurek Melnyk, PhD, APRN-CNP, FAANP, FNAP, FAAN, 2021-09-23 Assessment and Diagnosis Review for Advanced Practice Nursing Certification Exams is designed to help nurse practitioner students strengthen their assessment and clinical-reasoning skills in preparation for certification exams, clinical rotations, and clinical practice. This must-have resource is relevant for the AANPCB and ANCC Family Nurse Practitioner and Adult-Gerontology Primary Care Nurse Practitioner exams, ANCC Psychiatric-Mental Health Nurse Practitioner exam, and PNCB Pediatric Nurse Practitioner Primary Care exam. It includes both review content and practice Q&A—everything you need to pass the exam. It includes comprehensive coverage of pediatric, pregnant, and older adult populations, as well as social determinants of health and wellness and mental health and substance abuse. The review manual begins with evidence-based strategies for successful exam performance and tips for self-care. Each systems-based chapter includes an overview of anatomy and physiology; physical examination; differentials for episodic, acute, and chronic conditions; and wellness and preventive care considerations. Knowledge and application of key concepts are reinforced with numerous illustrations, tables, red flag boxes, evidence-based practice considerations, and end-of-chapter assessment questions. The review concludes with a 150-question practice test that addresses all patient populations and a 50-question practice for the pediatric population. With a total of 350 practice questions and detailed review content and answer rationales, Assessment and Diagnosis Review for Advanced Practice Nursing Certification Exams gives you the tools to study your way and the confidence to pass the first time, guaranteed. Key Features: Prepares APRN students for the assessment and diagnosis portions of their AANPCB, ANCC, and PNCB certification exams Provides a comprehensive yet concise review of the assessment of all body systems, as well as social determinants of health and mental health and substance abuse Includes coverage of pediatric, pregnant, and older adult populations Features abundant illustrations, tables, and boxes to facilitate information retention Includes a total of 350 exam-style questions with robust rationales, including two practice tests The American Academy of Nurse Practitioners Certification Board (AANPCB), American Nurses Credentialing Center (ANCC), and Pediatric Nursing Certification Board (PNCB) are the sole owners of their certification programs. AANPCB, ANCC, and PNCB do not endorse this exam preparation resource, nor do they have a proprietary relationship with Springer Publishing Company. |
| certified data science practitioner: Learn By Examples - Introduction to Data and Text Mining using DSTK3 Eric M. H. Goh , DSTK - Data Science Toolkit 3 is a set of data and text mining softwares, following the CRISP DM model. DSTK offers data understanding using statistical and text analysis, data preparation using normalization and text processing, modeling and evaluation for machine learning and statistical learning algorithms. DSTK 3 contains DSTK Engine as interpreter, DSTK ScriptWriter as a simple IDE, DSTK Studio providing a SPSS Statistics like easy to use interface with DSTK Engine, and DSTK Text Explorer provides a GUI for Text Mining. DSTK Studio and DSTK Text Explorer, however, need a small payment of 59 usd to support our development. DSTK Engine and DSTK ScriptWriter are free. This book is going to be an easy guide to get started using DSTK 3 softwares for data and text mining. Introduction Getting Started DSTK ScriptWriter Essentials DSTK Studio Essentials DSTK Text Explorer Essentials Conclusion This book has been taught at Udemy and EMHAcademy.com. Use the following Link to get the Udemy Course for FREE: https://www.udemy.com/introduction-to-data-and-text-mining-using-dstk-3/learn/v4/ |
Certified Data Science Practitioner™ (CDSP) (Exam DSP-210)
• Use data science principles to address business issues. • Apply the extract, transform, and load (ETL) process to prepare datasets. • Use multiple techniques to analyze data and extract …
Certified Data Science Practitioner - tcworkshop.com
In this course, you will implement data science techniques to address business issues. Use data science principles to address business issues. Apply the extract, transform, and load (ETL) …
COURSE OUTLINE CN-CDSP CERTIFIED DATA SCIENCE …
This course is also designed to assist students in preparing for the CertNexus® Certified Data SciencePractitioner™ (CDSP) (Exam DSP-210) certification.
Certified Data Science Practitioner (CDSP) - koenig …
Certified Data Science Practitioner (CDSP) Lesson 1: Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Lesson 2: …
Prerequisites For: Certified Data Science Practitioner (CDSP
The Certified Data Science Practitioner exam is designed for professionals across different industries seeking to demonstrate the ability to gain insights and build predictive models from …
Certified Data Science Practitioner Full PDF - archive.ncarb.org
Certified Data Science Practitioner: Practitioner’s Guide to Data Science Nasir Ali Mirza,2022-01-17 Covers Data Science concepts processes and the real world hands on use cases KEY FEATURES …
Certified Data Science Practitioner (CDSP) Exam DSP-210
Dec 21, 2023 · The Certified Data Science PractitionerTM (CDSP) exam is designed for professionals across different industries seeking to demonstrate the ability to gain insights and …
Certified Data Science Practitioner™ (CDSP) (Exam DSP-210) …
The Certified Data Science Practitioner™ (CDSP) (Exam DSP-210) course: • Reflects changes and updates to the field of data science, including the push to democratize data in the organization. • …
Certified Data Science Practitioner (CSDP)
In this course, you will implement data science techniques in order to address business issues. You will: Use data science principles to address business issues. Apply the extract, transform, and …
Certified Data Science Practitioner (DSP-110) Exam Blueprint
The Certified Data Science PractitionerTM (CDSP) exam is designed for professionals across different industries seeking to demonstrate the ability to gain insights and build predictive …
CertNexus Certified Data Science Practitioner
In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes …
Fact Sheet - CTU Training Solutions
making informed decisions. Data Science Practitioners take custody of data and make the data available in a structured form for the Data Scientist to use. They support the data life cycle by …
Certified Data Science Practitioner - archive.ncarb.org
Certified Data Science Practitioner: Practitioner’s Guide to Data Science Nasir Ali Mirza,2022-01-17 Covers Data Science concepts processes and the real world hands on use cases KEY FEATURES …
The Alliance for Data Science Professionals Guidance and …
Whilst there are two levels of certification associated with the Data Science standards. The standards will remain generic statements that can apply across a wide range of roles within the …
Certified Data Science Practitioner (CDSP) (Exam DSP-110)
• Use data science principles to address business issues. • Apply the extract, transform, and load (ETL) process to prepare datasets. • Use multiple techniques to analyze data and extract …
Certified Data Science Practitioner (CDSP) (Exam DSP-110)
• Use data science principles to address business issues. • Apply the extract, transform, and load (ETL) process to prepare datasets. • Use multiple techniques to analyze data and extract …
Certified Data Science Practitioner (book) - archive.ncarb.org
Certified Data Science Practitioner: Practitioner’s Guide to Data Science Nasir Ali Mirza,2022-01-17 Covers Data Science concepts processes and the real world hands on use cases KEY FEATURES …
Certified Data Science Practitioner Continuing Education Program
This document identifies the details of the continuing education program for CertNexus’ Certified Data Science Practitioner (CDSP) certification. This program is based on both research of …
Certified Data Science Practitioner (CDSP) (Exam DSP-110)
Certified Data Science Practitioner (CDSP) (Exam DSP-110) Certified Data Science Practitioner (CDSP) (Exam DSP-110) 01 Apr 2023. 1.3.4.5.6.2.7. 1 About This Course 2 Addressing Business …
CertNexus Certified Data Science Practitioner (CDSP) Exam …
Exam Options: Online through Pearson OnVUE or in person at Pearson VUE test centers. The Certified Data Science Practitioner exam is designed for professionals across different industries …
Certified Data Science Practitioner™ (CDSP) (Exam DSP-210)
• Use data science principles to address business issues. • Apply the extract, transform, and load (ETL) process to prepare datasets. • Use multiple techniques to analyze data and extract …
Certified Data Science Practitioner - tcworkshop.com
In this course, you will implement data science techniques to address business issues. Use data science principles to address business issues. Apply the extract, transform, and load (ETL) …
COURSE OUTLINE CN-CDSP CERTIFIED DATA SCIENCE …
This course is also designed to assist students in preparing for the CertNexus® Certified Data SciencePractitioner™ (CDSP) (Exam DSP-210) certification.
Certified Data Science Practitioner (CDSP) - koenig …
Certified Data Science Practitioner (CDSP) Lesson 1: Addressing Business Issues with Data Science Topic A: Initiate a Data Science Project Topic B: Formulate a Data Science Problem Lesson 2: …
Prerequisites For: Certified Data Science Practitioner (CDSP …
The Certified Data Science Practitioner exam is designed for professionals across different industries seeking to demonstrate the ability to gain insights and build predictive models from …
Certified Data Science Practitioner Full PDF
Certified Data Science Practitioner: Practitioner’s Guide to Data Science Nasir Ali Mirza,2022-01-17 Covers Data Science concepts processes and the real world hands on use cases KEY FEATURES …
Certified Data Science Practitioner (CDSP) Exam DSP-210
Dec 21, 2023 · The Certified Data Science PractitionerTM (CDSP) exam is designed for professionals across different industries seeking to demonstrate the ability to gain insights and …
Certified Data Science Practitioner™ (CDSP) (Exam DSP …
The Certified Data Science Practitioner™ (CDSP) (Exam DSP-210) course: • Reflects changes and updates to the field of data science, including the push to democratize data in the organization. • …
Certified Data Science Practitioner (CSDP)
In this course, you will implement data science techniques in order to address business issues. You will: Use data science principles to address business issues. Apply the extract, transform, and …
Certified Data Science Practitioner (DSP-110) Exam …
The Certified Data Science PractitionerTM (CDSP) exam is designed for professionals across different industries seeking to demonstrate the ability to gain insights and build predictive …
CertNexus Certified Data Science Practitioner
In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes …
Fact Sheet - CTU Training Solutions
making informed decisions. Data Science Practitioners take custody of data and make the data available in a structured form for the Data Scientist to use. They support the data life cycle by …
Certified Data Science Practitioner - archive.ncarb.org
Certified Data Science Practitioner: Practitioner’s Guide to Data Science Nasir Ali Mirza,2022-01-17 Covers Data Science concepts processes and the real world hands on use cases KEY FEATURES …
The Alliance for Data Science Professionals Guidance and …
Whilst there are two levels of certification associated with the Data Science standards. The standards will remain generic statements that can apply across a wide range of roles within the …
Certified Data Science Practitioner (CDSP) (Exam DSP …
• Use data science principles to address business issues. • Apply the extract, transform, and load (ETL) process to prepare datasets. • Use multiple techniques to analyze data and extract …
Certified Data Science Practitioner (CDSP) (Exam DSP-110)
• Use data science principles to address business issues. • Apply the extract, transform, and load (ETL) process to prepare datasets. • Use multiple techniques to analyze data and extract …
Certified Data Science Practitioner (book) - archive.ncarb.org
Certified Data Science Practitioner: Practitioner’s Guide to Data Science Nasir Ali Mirza,2022-01-17 Covers Data Science concepts processes and the real world hands on use cases KEY FEATURES …
Certified Data Science Practitioner Continuing Education …
This document identifies the details of the continuing education program for CertNexus’ Certified Data Science Practitioner (CDSP) certification. This program is based on both research of …
Certified Data Science Practitioner (CDSP) (Exam DSP-110)
Certified Data Science Practitioner (CDSP) (Exam DSP-110) Certified Data Science Practitioner (CDSP) (Exam DSP-110) 01 Apr 2023. 1.3.4.5.6.2.7. 1 About This Course 2 Addressing Business …
CertNexus Certified Data Science Practitioner (CDSP) …
Exam Options: Online through Pearson OnVUE or in person at Pearson VUE test centers. The Certified Data Science Practitioner exam is designed for professionals across different industries …
