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Uplift Your Career & Skill Up to Your Dream Job - Learning Simplified From Home! Kickstart your career & boost your employability by helping you discover your skills, talents, and interests with our special Advanced Blockchain Coding Course. You'll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides the professional training that employers are looking for in today's workplaces. The Advanced Blockchain Coding Course is one of the most prestigious training offered at Skillwise and is highly valued by employers for good reason. This Advanced Blockchain Coding Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field. This Advanced Blockchain Coding Course, like every one of Skillwise's courses, is meticulously developed and well-researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly. At Skillwise, we don't just offer courses; we also provide a valuable teaching process. When you buy a course from Skillwise, you get unlimited Lifetime access with 24/7 dedicated tutor support. Why buy this Advanced Blockchain Coding? Unlimited access to the course forever Digital Certificate, Transcript, and student ID are all included in the price Absolutely no hidden fees Directly receive CPD-accredited qualifications after course completion Receive one-to-one assistance every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Advanced Blockchain Coding there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for free. Original Hard Copy certificates need to be ordered at an additional cost of £8. Who is this course for? This Advanced Blockchain Coding course is ideal for Students Recent graduates Job Seekers Anyone interested in this topic People already working in the relevant fields and want to polish their knowledge and skills. Prerequisites This Advanced Blockchain Coding does not require you to have any prior qualifications or experience. You can just enroll and start learning. This Advanced Blockchain Coding was made by professionals and it is compatible with all PCs, Macs, tablets, and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path As this course comes with multiple courses included as a bonus, you will be able to pursue multiple occupations. This Advanced Blockchain Coding is a great way for you to gain multiple skills from the comfort of your home. Advanced Blockchain Coding Module 01: Introduction 00:03:00 Module 02: The UTXO model 00:07:00 Module 03: Operations in Blockchain 00:06:00 Module 04: Ethereum operations 00:09:00 Module 05: Transaction integrity 00:05:00 Module 06: Smart contact processing 00:05:00 Module 07: Setting you up 00:10:00 Module 08: Remix 00:13:00 Module 09: Variables Part 01 00:11:00 Module 10: Variables Part 02 00:06:00 Module 11: Variables Theory 00:05:00 Module 12: Mappings 00:07:00 Module 13: Structures and arrays 00:10:00 Module 14: Enums and their working 00:06:00 Module 15: Theory of mappings and user-defined data types 00:08:00 Module 16: Functions and Error handling 00:10:00 Module 17: Code the functions 00:05:00 Module 18: Common Errors 00:07:00 Module 19: Error Handling 00:16:00 Module 20: Important properties of Solidity 00:07:00 Module 21: Inheritance and Importing 00:05:00 Module 22: Coding, importing and inheriting 00:11:00 Module 23: Project - Distributed wallet 00:10:00 Module 24: Project Coding Part 01 00:05:00 Module 25: Project Coding Part 02 00:09:00 Module 26: Project Coding Part 03 00:11:00 Module 27: Project Coding Part 04 00:08:00 Module 28: Project Coding Part 05 00:08:00 Module 29: Theory of events 00:05:00 Module 30: Practical Implementation of events 00:05:00 Module 31: Conclusion 00:02:00 Assignment Assignment -Advanced Blockchain Coding 06:06:00 Order Your Certificate Order Your Certificate QLS

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Course Overview Peek into the world of data science and machine learning with the comprehensive Data Science & Machine Learning With R in 2021 course. This course will provide you with a detailed understanding of both machine learning and data science. In addition, you will acquire essential skills to pursue a career in this growing industry. The Data Science & Machine Learning With R in 2021 course will teach you the core concept of data science. You will be able to recognize different data types and structures. From the modules, you will receive an introduction to the intermediate R Section. The course will show you the techniques of data manipulation in R. You will know the process of data visualization with R and learn to create reports with R markdown. The Data Science & Machine Learning With R in 2021 course will provide you with an insight into the fundamentals of machine learning. You will understand the principles of data processing, linear regression, logistic regression and more.  This highly informative Data Science & Machine Learning With R in 2021 course will equip you with the essential skills of data science. If you desire to become a professional data scientist, this course can be your stepping stone. So, enroll in the course and fast track your career. Learning Outcomes Learn the definition of data science Understand the basics of machine learning Enrich your knowledge of data types and structures Know the process of data manipulation in R Gain the ability to create reports with R markdown Become skilled in building web apps with R shiny Who is this course for? Aspiring data scientists or individuals interested in learning data science and machine learning  Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path  The Data Science & Machine Learning With R in 2021 course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Data Scientist Data Science and Machine Learning Course Intro Data Science and Machine Learning Introduction 00:03:00 What is Data Science 00:10:00 Machine Learning Overview 00:05:00 Who is This Course for 00:03:00 Data Science and Machine Learning Marketplace 00:05:00 Data Science and Machine Learning Job Opportunities 00:03:00 Data Types and Structures in R Getting Started 00:16:00 Basics 00:06:00 Files 00:11:00 RStudio 00:07:00 Tidyverse 00:05:00 Resources 00:04:00 Data Types and Structures in R Unit Introduction 00:30:00 Basic Type 00:09:00 Vector Part One 00:20:00 Vectors Part Two 00:25:00 Vectors - Missing Values 00:16:00 Vectors - Coercion 00:14:00 Vectors - Naming 00:10:00 Vectors - Misc 00:06:00 Creating Matrics 00:31:00 List 00:32:00 Introduction to Data Frames 00:19:00 Creating Data Frames 00:20:00 Data Frames: Helper Functions 00:31:00 Data Frames Tibbles 00:39:00 Intermediate R Intermediate Introduction 00:47:00 Relational Operations 00:11:00 Conditional Statements 00:11:00 Loops 00:08:00 Functions 00:14:00 Packages 00:11:00 Factors 00:28:00 Dates and Times 00:30:00 Functional Programming 00:37:00 Data Import or Export 00:22:00 Database1 00:27:00 Data Manipulation in R Data Manipulation in R Introduction 00:36:00 Tidy Data 00:11:00 The Pipe Operator 00:15:00 The Filter Verb 00:22:00 The Select Verb 00:46:00 The Mutate Verb 00:32:00 The Arrange Verb 00:10:00 The Summarize Verb 00:23:00 Data Pivoting 00:43:00 JSON Parsing 00:11:00 String Manipulation 00:33:00 Web Scraping 00:59:00 Data Visualization in R Data Visualization in R Section Intro 00:17:00 Getting Started 00:16:00 Aesthetics Mappings 00:25:00 Single Variable Plots 00:37:00 Two Variable Plots 00:21:00 Facets, Layering, and Coordinate Systems 00:18:00 Styling and Saving 00:12:00 Creating Reports with R Markdown Creating with R Markdown 00:29:00 Building Webapps with R Shiny Introduction to R Shiny 00:26:00 A Basic R Shiny App 00:31:00 Other Examples with R Shiny 00:34:00 Introduction to Machine Learning Machine Learning Part 1 00:22:00 Machine Learning Part 2 00:47:00 Starting A Career in Data Science Starting a Data Science Career Section Overview 00:03:00 Data Science Resume 00:04:00 Getting Started with Freelancing 00:05:00 Top Freelance Websites 00:05:00 Personal Branding 00:05:00 Importance of Website and Blo 00:04:00 Networking Do's and Don'ts 00:04:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

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Overview This comprehensive course on Advanced Blockchain Coding will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Advanced Blockchain Coding comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Advanced Blockchain Coding. It is available to all students, of all academic backgrounds. Requirements Our Advanced Blockchain Coding is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 2 sections • 32 lectures • 03:55:00 total length •Module 01: Introduction: 00:03:00 •Module 02: The UTXO model: 00:07:00 •Module 03: Operations in Blockchain: 00:06:00 •Module 04: Ethereum operations: 00:09:00 •Module 05: Transaction integrity: 00:05:00 •Module 06: Smart contact processing: 00:05:00 •Module 07: Setting you up: 00:10:00 •Module 08: Remix: 00:13:00 •Module 09: Variables Part 01: 00:11:00 •Module 10: Variables Part 02: 00:06:00 •Module 11: Variables Theory: 00:05:00 •Module 12: Mappings: 00:07:00 •Module 13: Structures and arrays: 00:10:00 •Module 14: Enums and their working: 00:06:00 •Module 15: Theory of mappings and user-defined data types: 00:08:00 •Module 16: Functions and Error handling: 00:10:00 •Module 17: Code the functions: 00:05:00 •Module 18: Common Errors: 00:07:00 •Module 19: Error Handling: 00:16:00 •Module 20: Important properties of Solidity: 00:07:00 •Module 21: Inheritance and Importing: 00:05:00 •Module 22: Coding, importing and inheriting: 00:11:00 •Module 23: Project - Distributed wallet: 00:10:00 •Module 24: Project Coding Part 01: 00:05:00 •Module 25: Project Coding Part 02: 00:09:00 •Module 26: Project Coding Part 03: 00:11:00 •Module 27: Project Coding Part 04: 00:08:00 •Module 28: Project Coding Part 05: 00:08:00 •Module 29: Theory of events: 00:05:00 •Module 30: Practical Implementation of events: 00:05:00 •Module 31: Conclusion: 00:02:00 •Assignment - Advanced Blockchain Coding: 00:00:00

Overview This comprehensive course on Data Science & Machine Learning with R will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Data Science & Machine Learning with R comes with accredited certification, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Data Science & Machine Learning with R. It is available to all students, of all academic backgrounds. Requirements Our Data Science & Machine Learning with R is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 10 sections • 69 lectures • 22:07:00 total length •Data Science and Machine Learning Introduction: 00:03:00 •What is Data Science: 00:10:00 •Machine Learning Overview: 00:05:00 •Who is This Course for: 00:03:00 •Data Science and Machine Learning Marketplace: 00:05:00 •Data Science and Machine Learning Job Opportunities: 00:03:00 •Getting Started: 00:11:00 •Basics: 00:06:00 •Files: 00:11:00 •RStudio: 00:07:00 •Tidyverse: 00:05:00 •Resources: 00:04:00 •Unit Introduction: 00:30:00 •Basic Type: 00:09:00 •Vector Part One: 00:20:00 •Vectors Part Two: 00:25:00 •Vectors - Missing Values: 00:16:00 •Vectors - Coercion: 00:14:00 •Vectors - Naming: 00:10:00 •Vectors - Misc: 00:06:00 •Creating Matrics: 00:31:00 •List: 00:32:00 •Introduction to Data Frames: 00:19:00 •Creating Data Frames: 00:20:00 •Data Frames: Helper Functions: 00:31:00 •Data Frames Tibbles: 00:39:00 •Intermediate Introduction: 00:47:00 •Relational Operations: 00:11:00 •Conditional Statements: 00:11:00 •Loops: 00:08:00 •Functions: 00:14:00 •Packages: 00:11:00 •Factors: 00:28:00 •Dates and Times: 00:30:00 •Functional Programming: 00:37:00 •Data Import or Export: 00:22:00 •Database: 00:27:00 •Data Manipulation in R Introduction: 00:36:00 •Tidy Data: 00:11:00 •The Pipe Operator: 00:15:00 •The Filter Verb: 00:22:00 •The Select Verb: 00:46:00 •The Mutate Verb: 00:32:00 •The Arrange Verb: 00:10:00 •The Summarize Verb: 00:23:00 •Data Pivoting: 00:43:00 •JSON Parsing: 00:11:00 •String Manipulation: 00:33:00 •Web Scraping: 00:59:00 •Data Visualization in R Section Intro: 00:17:00 •Getting Started: 00:16:00 •Aesthetics Mappings: 00:25:00 •Single Variable Plots: 00:37:00 •Two Variable Plots: 00:21:00 •Facets, Layering, and Coordinate Systems: 00:18:00 •Styling and Saving: 00:12:00 •Creating with R Markdown: 00:29:00 •Introduction to R Shiny: 00:26:00 •A Basic R Shiny App: 00:31:00 •Other Examples with R Shiny: 00:34:00 •Machine Learning Part 1: 00:22:00 •Machine Learning Part 2: 00:47:00 •Starting a Data Science Career Section Overview: 00:03:00 •Data Science Resume: 00:04:00 •Getting Started with Freelancing: 00:05:00 •Top Freelance Websites: 00:05:00 •Personal Branding: 00:05:00 •Importance of Website and Blo: 00:04:00 •Networking Do's and Don'ts: 00:04:00

Overview In the era where information is abundant and decisions are driven by data, have you ever pondered, 'what is machine learning?' or 'what is data science?' Dive into the realm of 'Data Science & Machine Learning with R from A-Z,' a comprehensive guide to unravel these complexities. This course effortlessly blends the foundational aspects of data science with the intricate depths of machine learning algorithms, all through the versatile medium of R. As the digital economy booms, the demand for machine learning jobs continues to surge. Equip yourself with the proficiency to navigate this dynamic field and transition from being an inquisitive mind to a sought-after professional in the space of data science and machine learning with R. Learning Outcomes: Understand the foundational concepts of data science and machine learning. Familiarise oneself with the R environment and its functionalities. Master data types, structures, and advanced techniques in R. Acquire proficiency in data manipulation and visual representation using R. Generate comprehensive reports using R Markdown and design web applications with R Shiny. Gain a thorough understanding of machine learning methodologies and their applications. Gain insights into initiating a successful career in the data science sector. Why buy this Data Science & Machine Learning with R from A-Z course? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Data Science & Machine Learning with R from A-Z there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Data Science & Machine Learning with R from A-Z course for? This course is ideal for Individuals keen on exploring the intricacies of machine learning and data science. Aspiring data analysts and scientists looking to specialise in Machine Learning with R. IT professionals aiming to diversify their skill set in the emerging data-driven market. Researchers seeking to harness the power of R for data representation and analysis. Academics and students aiming to bolster their understanding of modern data practices with R. Prerequisites This Data Science & Machine Learning with R from A-Z does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Data Science & Machine Learning with R from A-Z was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Scientist - Average salary range: £35,000 - £70,000 Per Annum Machine Learning Engineer - Average salary range: £50,000 - £80,000 Per Annum Data Analyst - Average salary range: £28,000 - £55,000 Per Annum R Developer - Average salary range: £30,000 - £60,000 Per Annum R Shiny Web Developer - Average salary range: £32,000 - £65,000 Per Annum Machine Learning Researcher - Average salary range: £40,000 - £75,000 Per Annum Course Curriculum Data Science and Machine Learning Course Intro Data Science and Machine Learning Introduction 00:03:00 What is Data Science 00:10:00 Machine Learning Overview 00:05:00 Who is This Course for 00:03:00 Data Science and Machine Learning Marketplace 00:05:00 Data Science and Machine Learning Job Opportunities 00:03:00 Getting Started with R Getting Started 00:11:00 Basics 00:06:00 Files 00:11:00 RStudio 00:07:00 Tidyverse 00:05:00 Resources 00:04:00 Data Types and Structures in R Unit Introduction 00:30:00 Basic Type 00:09:00 Vector Part One 00:20:00 Vectors Part Two 00:25:00 Vectors - Missing Values 00:16:00 Vectors - Coercion 00:14:00 Vectors - Naming 00:10:00 Vectors - Misc 00:06:00 Creating Matrics 00:31:00 List 00:32:00 Introduction to Data Frames 00:19:00 Creating Data Frames 00:20:00 Data Frames: Helper Functions 00:31:00 Data Frames Tibbles 00:39:00 Intermediate R Intermediate Introduction 00:47:00 Relational Operations 00:11:00 Conditional Statements 00:11:00 Loops 00:08:00 Functions 00:14:00 Packages 00:11:00 Factors 00:28:00 Dates and Times 00:30:00 Functional Programming 00:37:00 Data Import or Export 00:22:00 Database 00:27:00 Data Manipulation in R Data Manipulation in R Introduction 00:36:00 Tidy Data 00:11:00 The Pipe Operator 00:15:00 The Filter Verb 00:22:00 The Select Verb 00:46:00 The Mutate Verb 00:32:00 The Arrange Verb 00:10:00 The Summarize Verb 00:23:00 Data Pivoting 00:43:00 JSON Parsing 00:11:00 String Manipulation 00:33:00 Web Scraping 00:59:00 Data Visualization in R Data Visualization in R Section Intro 00:17:00 Getting Started 00:16:00 Aesthetics Mappings 00:25:00 Single Variable Plots 00:37:00 Two Variable Plots 00:21:00 Facets, Layering, and Coordinate Systems 00:18:00 Styling and Saving 00:12:00 Creating Reports with R Markdown Creating with R Markdown 00:29:00 Building Webapps with R Shiny Introduction to R Shiny 00:26:00 A Basic R Shiny App 00:31:00 Other Examples with R Shiny 00:34:00 Introduction to Machine Learning Machine Learning Part 1 00:22:00 Machine Learning Part 2 00:47:00 Starting A Career in Data Science Starting a Data Science Career Section Overview 00:03:00 Data Science Resume 00:04:00 Getting Started with Freelancing 00:05:00 Top Freelance Websites 00:05:00 Personal Branding 00:05:00 Importance of Website and Blo 00:04:00 Networking Do's and Don'ts 00:04:00 Assignment Assignment - Data Science & Machine Learning with R 00:00:00

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Duration 2 Days 12 CPD hours This course is intended for vSphere administrators, architects, system engineers, and systems integrators who are responsible for the deployment or management of Site Recovery Manager Overview By the end of the course, you should be able to meet the following objectives: Summarize the components of Site Recovery Manager architecture Deploy and configure the Site Recovery Manager appliance Describe the principal disaster recovery topologies that are used with Site Recovery Manager Configure inventory and resource mappings Describe the storage replication options that are used with Site Recovery Manager Configure Site Recovery Manager to leverage array-based replication Describe VMware vSphere Replication™ functionality Describe the vSphere Replication architecture Deploy and configure vSphere Replication for use with Site Recovery Manager Build Site Recovery Manager protection groups based on vSphere Replication Build, edit, execute, test, and remove a recovery plan Perform a planned migration Perform reprotect and failback using Site Recovery Manager and vSphere Replication This hands-on training course gives experienced VMware vSphere© administrators the knowledge to install, configure, and manage VMware Site Recovery Manager? 8.2. This course also shows you how to write and test disaster recovery plans that use Site Recovery Manager. Course Introduction Outline the necessary information to effectively undertake this course Identify resources for additional information Overview and Architecture Discuss Site Recovery Manager architecture Examine disaster recovery options with Site Recovery Manager Describe Site Recovery Manager integration with VMware vSphere© ClientTM Discuss Site Recovery Manager features Analyze Site Recovery Manager storage policies and integration options Discuss how Site Recovery Manager supports several disaster recovery topologies identify use cases for Site Recovery Manager across various scenarios Describe how VMware Site Recovery? for VMware Cloud? on AWS integrates with Site Recovery Manager. Deploy & Configure Site Recovery Manager Identify the requirements to deploy Site Recovery Manager Discuss the benefits of the Site Recovery Manager appliance Explore vSphere deployment models Deploy the Site Recovery Manager appliance Navigate the Site Recovery Manager configuration user interface Describe the process to register Site Recovery Manager with VMware vCenter Server© Configure site pairing Identify how to perform updates to the Site Recovery Manager appliance Configuring Inventory Mappings Outline the importance of inventory mappings Examine configuration options for inventory mappings Outline the importance of placeholders Using Array-based Replication Describe array-based replication Discuss the role of the Storage Replication Adapter (SRA) Explore the relationship between devices, consistency groups and datastore groups Configure array pairs vSphere Replication Explore vSphere Replication architecture Examine vSphere Replication functionality Formulate use cases for vSphere Replication Deploy a vSphere Replication appliance Configure vSphere Replication appliance settings Configure a vSphere Replication appliance connection Deploy a vSphere Replication server Register a vSphere Replication server Replicating Virtual Machines with vSphere Replication Configure vSphere Replication for virtual machines Explain the importance of datastore mappings Describe vSphere Replication recovery point objective scheduling Describe the vSphere Replication disk transfer protocol Building Protection Groups Define protection group functionality Examine the differences between array-based protection groups, protection groups based on vSphere Replication, and storage profile protection groups Create a protection group Discuss protection group settings Remove protection from a virtual machine Create a storage profile protection group Building Recovery Plans Discuss recovery plan concepts List recovery plan steps Discuss network planning Discuss customization options in recovery planning Outline how to implement a recovery plan Investigate recovery plan options Testing and Running a Recovery Plan Discuss use cases for Site Recovery Manager Describe planned migration Identify Site Recovery Manager workflows Discuss the importance of VMware vSphere© VMFS resignaturing Examine Site Recovery Manager integration with various vSphere technologies Outline how to conduct a recovery plan test Perform recovery plan test execution Identify the effects on the storage layer during recovery steps Explain a recovery plan execution in planned migration or disaster recovery mode Understand storage layer changes for plan execution types Identify the recovery steps for each execution type Describe how to reprotect a data center Examine failback steps Monitoring and Troubleshooting Discuss Site Recovery Manager alarms Explore Site Recovery Manager history reports Configuring advanced Site Recovery Manager settings Describe how to modify logging levels Explain how to collect log bundles Identify key log locations