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Duration 5 Days 30 CPD hours This course is intended for This course is intended for anyone who is new to software development and wants, or needs, to gain an understanding of the fundamentals of coding and basics of C++ and object-oriented programming concepts. This course is for Non-Developers, or anyone who wants to have a basic understanding of and learn how to code C++ applications and syntax Overview Companies are constantly challenged to keep their applications, development projects, products, services (and programmers!) up to speed with the latest industry tools, skills, technologies and practices to stay ahead in the ever-shifting markets that make up today's fiercely competitive business landscape. The need for application, web and mobile developers and coders is seemingly endless as technologies regularly change and grow to meet the modern needs of demanding industries and clients. C++ and Programming Basics for Non-Programmers is a five-day, basic-level training course geared for IT candidates who have little or no prior experience in computer programming. Throughout this gentle introduction to programming and C++, students will learn to create applications and libraries using C++ using best practices and sound OO development techniques for writing object-oriented programs in C++. Special emphasis is placed on object-oriented concepts and best practices throughout the training. Fundamentals of the Program Development Cycle Computer Architecture The Notion of Algorithms Source Code vs. Machine Code Compile-Time vs. Run-Time Software Program Architecture Standalone Client/Server Distributed Web-Enabled IDE (Interactive Development Environment) Concepts Looping Constructs Counter-Controlled Repetition Sentinel-Controlled Repetition Nested Control Constructs break and continue Statements Structured Programming Best Practices Writing Methods (Functions) Static vs. Dynamic Allocation Declaring Methods Declaring Methods with Multiple Parameters Method-Call Stack Scope of Declarations Argument Promotion and Casting Designing Methods for Reusability Method Overloading Arrays Purpose of Arrays Declaring and Instantiating Arrays Passing Arrays to Methods Multidimensional Arrays Variable-Length Argument Lists Using Command-Line Arguments Using Environment Variables Deeper Into Classes and Objects Controlling Access to Class Members Referencing the Current Object Using this Overloading Constructors Default and No-Argument Constructors Composition of Classes Garbage Collection and Destructors The finalize Method Static Class Members Defining Classes Using Inheritance Application Development Fundamentals Structure of a C++ Program Memory Concepts Fundamental Data Type Declarations Fundamental I/O Concepts Fundamental Operators Arithmetic Operators Logical Operators Precedence and Associativity Building and Deploying a C++ Program Superclasses and Subclasses Advantages of Using Inheritance protected Class Members Constructors in Subclasses Increasing Convenience by Using Polymorphism Purpose of Polymorphic Behavior The Concept of a Signature Abstract Classes and Methods final Methods and Classes Purpose of Interfaces Using and Creating Interfaces Common Interfaces of the C++ API Files and Streams Concept of a Stream Class File Sequential Access Object Serialization to/from Sequential Access Files Fundamental Searching and Sorting Introduction to Searching Algorithms Linear Search Binary Search Introduction to Sorting Algorithms Selection Sort Insertion Sort Merge Sort Fundamental Data Structures Dynamic Memory Allocation Linked Lists Stacks Queues Trees Exception Handling Types of Exceptions Exception Handling Overview Introduction to Classes and Objects Classes, Objects and Methods Object Instances Declaring and Instantiating a C++ Object Declaring Methods set and get Methods Initiating Objects with Constructors Primitive Types vs. Reference Types Flow Control Conditional Constructs Exception Class Hierarchy Extending Exception Classes When to Throw or Assert Exceptions Formatted Output printf Syntax Conversion Characters Specifying Field Width and Precision Using Flags to Alter Appearance Printing Literals and Escape Sequences Formatting Output with Class Formatter Strings, Characters and Regular Expressions Fundamentals of Characters and Strings String Class String Operations StringBuilder Class Character Class StringTokenizer Class Regular Expressions Regular Expression Syntax Pattern Class Matcher Class Fundamental GUI Programming Concepts Overview of Swing Components Displaying Text and Graphics in a Window Event Handling with Nested Classes GUI Event Types and Listener Interfaces Mouse Event Handling Layout Managers Additional course details: Nexus Humans C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the C Plus Plus and Programming Basics for Non-Programmers (TTCP2000) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

The 'Complete Python Machine Learning & Data Science Fundamentals' course covers the foundational concepts of machine learning, data science, and Python programming. It includes hands-on exercises, data visualization, algorithm evaluation techniques, feature selection, and performance improvement using ensembles and parameter tuning. Learning Outcomes: Understand the fundamental concepts and types of machine learning, data science, and Python programming. Learn to prepare the system and environment for data analysis and machine learning tasks. Master the basics of Python, NumPy, Matplotlib, and Pandas for data manipulation and visualization. Gain insights into dataset summary statistics, data visualization techniques, and data preprocessing. Explore feature selection methods and evaluation metrics for classification and regression algorithms. Compare and select the best machine learning model using pipelines and ensembles. Learn to export, save, load machine learning models, and finalize the chosen models for real-time predictions. Why buy this Complete Python Machine Learning & Data Science Fundamentals? 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 Complete Python Machine Learning & Data Science Fundamentals 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 course for? This Complete Python Machine Learning & Data Science Fundamentals 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 skill. Prerequisites This Complete Python Machine Learning & Data Science Fundamentals does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Complete Python Machine Learning & Data Science Fundamentals 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 As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Complete Python Machine Learning & Data Science Fundamentals is a great way for you to gain multiple skills from the comfort of your home. Course Curriculum Course Overview & Table of Contents Course Overview & Table of Contents 00:09:00 Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 00:05:00 Introduction to Machine Learning - Part 2 - Classifications and Applications Introduction to Machine Learning - Part 2 - Classifications and Applications 00:06:00 System and Environment preparation - Part 1 System and Environment preparation - Part 1 00:08:00 System and Environment preparation - Part 2 System and Environment preparation - Part 2 00:06:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 1 00:10:00 Learn Basics of python - Assignment Learn Basics of python - Assignment 2 00:09:00 Learn Basics of python - Functions Learn Basics of python - Functions 00:04:00 Learn Basics of python - Data Structures Learn Basics of python - Data Structures 00:12:00 Learn Basics of NumPy - NumPy Array Learn Basics of NumPy - NumPy Array 00:06:00 Learn Basics of NumPy - NumPy Data Learn Basics of NumPy - NumPy Data 00:08:00 Learn Basics of NumPy - NumPy Arithmetic Learn Basics of NumPy - NumPy Arithmetic 00:04:00 Learn Basics of Matplotlib Learn Basics of Matplotlib 00:07:00 Learn Basics of Pandas - Part 1 Learn Basics of Pandas - Part 1 00:06:00 Learn Basics of Pandas - Part 2 Learn Basics of Pandas - Part 2 00:07:00 Understanding the CSV data file Understanding the CSV data file 00:09:00 Load and Read CSV data file using Python Standard Library Understanding the CSV data file 00:09:00 Load and Read CSV data file using NumPy Load and Read CSV data file using Python Standard Library 00:09:00 Load and Read CSV data file using Pandas Load and Read CSV data file using Pandas 00:05:00 Dataset Summary - Peek, Dimensions and Data Types Dataset Summary - Peek, Dimensions and Data Types 00:09:00 Dataset Summary - Class Distribution and Data Summary Dataset Summary - Class Distribution and Data Summary 00:09:00 Dataset Summary - Explaining Correlation Dataset Summary - Explaining Correlation 00:11:00 Dataset Summary - Explaining Skewness - Gaussian and Normal Curve Dataset Summary - Explaining Skewness - Gaussian and Normal Curve 00:07:00 Dataset Visualization - Using Histograms Dataset Visualization - Using Histograms 00:07:00 Dataset Visualization - Using Density Plots Dataset Visualization - Using Density Plots 00:06:00 Dataset Visualization - Box and Whisker Plots Dataset Visualization - Box and Whisker Plots 00:05:00 Multivariate Dataset Visualization - Correlation Plots Multivariate Dataset Visualization - Correlation Plots 00:08:00 Multivariate Dataset Visualization - Scatter Plots Multivariate Dataset Visualization - Scatter Plots 00:05:00 Data Preparation (Pre-Processing) - Introduction Data Preparation (Pre-Processing) - Introduction 00:09:00 Data Preparation - Re-scaling Data - Part 1 Data Preparation - Re-scaling Data - Part 1 00:09:00 Data Preparation - Re-scaling Data - Part 2 Data Preparation - Re-scaling Data - Part 2 00:09:00 Data Preparation - Standardizing Data - Part 1 Data Preparation - Standardizing Data - Part 1 00:07:00 Data Preparation - Standardizing Data - Part 2 Data Preparation - Standardizing Data - Part 2 00:04:00 Data Preparation - Normalizing Data Data Preparation - Normalizing Data 00:08:00 Data Preparation - Binarizing Data Data Preparation - Binarizing Data 00:06:00 Feature Selection - Introduction Feature Selection - Introduction 00:07:00 Feature Selection - Uni-variate Part 1 - Chi-Squared Test Feature Selection - Uni-variate Part 1 - Chi-Squared Test 00:09:00 Feature Selection - Uni-variate Part 2 - Chi-Squared Test Feature Selection - Uni-variate Part 2 - Chi-Squared Test 00:10:00 Feature Selection - Recursive Feature Elimination Feature Selection - Recursive Feature Elimination 00:11:00 Feature Selection - Principal Component Analysis (PCA) Feature Selection - Principal Component Analysis (PCA) 00:09:00 Feature Selection - Feature Importance Feature Selection - Feature Importance 00:07:00 Refresher Session - The Mechanism of Re-sampling, Training and Testing Refresher Session - The Mechanism of Re-sampling, Training and Testing 00:12:00 Algorithm Evaluation Techniques - Introduction Algorithm Evaluation Techniques - Introduction 00:07:00 Algorithm Evaluation Techniques - Train and Test Set Algorithm Evaluation Techniques - Train and Test Set 00:11:00 Algorithm Evaluation Techniques - K-Fold Cross Validation Algorithm Evaluation Techniques - K-Fold Cross Validation 00:09:00 Algorithm Evaluation Techniques - Leave One Out Cross Validation Algorithm Evaluation Techniques - Leave One Out Cross Validation 00:05:00 Algorithm Evaluation Techniques - Repeated Random Test-Train Splits Algorithm Evaluation Techniques - Repeated Random Test-Train Splits 00:07:00 Algorithm Evaluation Metrics - Introduction Algorithm Evaluation Metrics - Introduction 00:09:00 Algorithm Evaluation Metrics - Classification Accuracy Algorithm Evaluation Metrics - Classification Accuracy 00:08:00 Algorithm Evaluation Metrics - Log Loss Algorithm Evaluation Metrics - Log Loss 00:03:00 Algorithm Evaluation Metrics - Area Under ROC Curve Algorithm Evaluation Metrics - Area Under ROC Curve 00:06:00 Algorithm Evaluation Metrics - Confusion Matrix Algorithm Evaluation Metrics - Confusion Matrix 00:10:00 Algorithm Evaluation Metrics - Classification Report Algorithm Evaluation Metrics - Classification Report 00:04:00 Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction Algorithm Evaluation Metrics - Mean Absolute Error - Dataset Introduction 00:06:00 Algorithm Evaluation Metrics - Mean Absolute Error Algorithm Evaluation Metrics - Mean Absolute Error 00:07:00 Algorithm Evaluation Metrics - Mean Square Error Algorithm Evaluation Metrics - Mean Square Error 00:03:00 Algorithm Evaluation Metrics - R Squared Algorithm Evaluation Metrics - R Squared 00:04:00 Classification Algorithm Spot Check - Logistic Regression Classification Algorithm Spot Check - Logistic Regression 00:12:00 Classification Algorithm Spot Check - Linear Discriminant Analysis Classification Algorithm Spot Check - Linear Discriminant Analysis 00:04:00 Classification Algorithm Spot Check - K-Nearest Neighbors Classification Algorithm Spot Check - K-Nearest Neighbors 00:05:00 Classification Algorithm Spot Check - Naive Bayes Classification Algorithm Spot Check - Naive Bayes 00:04:00 Classification Algorithm Spot Check - CART Classification Algorithm Spot Check - CART 00:04:00 Classification Algorithm Spot Check - Support Vector Machines Classification Algorithm Spot Check - Support Vector Machines 00:05:00 Regression Algorithm Spot Check - Linear Regression Regression Algorithm Spot Check - Linear Regression 00:08:00 Regression Algorithm Spot Check - Ridge Regression Regression Algorithm Spot Check - Ridge Regression 00:03:00 Regression Algorithm Spot Check - Lasso Linear Regression Regression Algorithm Spot Check - Lasso Linear Regression 00:03:00 Regression Algorithm Spot Check - Elastic Net Regression Regression Algorithm Spot Check - Elastic Net Regression 00:02:00 Regression Algorithm Spot Check - K-Nearest Neighbors Regression Algorithm Spot Check - K-Nearest Neighbors 00:06:00 Regression Algorithm Spot Check - CART Regression Algorithm Spot Check - CART 00:04:00 Regression Algorithm Spot Check - Support Vector Machines (SVM) Regression Algorithm Spot Check - Support Vector Machines (SVM) 00:04:00 Compare Algorithms - Part 1 : Choosing the best Machine Learning Model Compare Algorithms - Part 1 : Choosing the best Machine Learning Model 00:09:00 Compare Algorithms - Part 2 : Choosing the best Machine Learning Model Compare Algorithms - Part 2 : Choosing the best Machine Learning Model 00:05:00 Pipelines : Data Preparation and Data Modelling Pipelines : Data Preparation and Data Modelling 00:11:00 Pipelines : Feature Selection and Data Modelling Pipelines : Feature Selection and Data Modelling 00:10:00 Performance Improvement: Ensembles - Voting Performance Improvement: Ensembles - Voting 00:07:00 Performance Improvement: Ensembles - Bagging Performance Improvement: Ensembles - Bagging 00:08:00 Performance Improvement: Ensembles - Boosting Performance Improvement: Ensembles - Boosting 00:05:00 Performance Improvement: Parameter Tuning using Grid Search Performance Improvement: Parameter Tuning using Grid Search 00:08:00 Performance Improvement: Parameter Tuning using Random Search Performance Improvement: Parameter Tuning using Random Search 00:06:00 Export, Save and Load Machine Learning Models : Pickle Export, Save and Load Machine Learning Models : Pickle 00:10:00 Export, Save and Load Machine Learning Models : Joblib Export, Save and Load Machine Learning Models : Joblib 00:06:00 Finalizing a Model - Introduction and Steps Finalizing a Model - Introduction and Steps 00:07:00 Finalizing a Classification Model - The Pima Indian Diabetes Dataset Finalizing a Classification Model - The Pima Indian Diabetes Dataset 00:07:00 Quick Session: Imbalanced Data Set - Issue Overview and Steps Quick Session: Imbalanced Data Set - Issue Overview and Steps 00:09:00 Iris Dataset : Finalizing Multi-Class Dataset Iris Dataset : Finalizing Multi-Class Dataset 00:09:00 Finalizing a Regression Model - The Boston Housing Price Dataset Finalizing a Regression Model - The Boston Housing Price Dataset 00:08:00 Real-time Predictions: Using the Pima Indian Diabetes Classification Model Real-time Predictions: Using the Pima Indian Diabetes Classification Model 00:07:00 Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset Real-time Predictions: Using Iris Flowers Multi-Class Classification Dataset 00:03:00 Real-time Predictions: Using the Boston Housing Regression Model Real-time Predictions: Using the Boston Housing Regression Model 00:08:00 Resources Resources - Python Machine Learning & Data Science Fundamentals 00:00:00

Mindfulness: Mindfulness Do you want to take the online Mindfulness Diploma Course?we have designed this specialized Mindfulness Diploma Course to assist those who are always overwhelmed and agitated. Mindfulness Diploma Courses content is designed to give useful insights and practical information. This Mindfulness Diploma Course has six modules to describes mindfulness and how to become a mindfulness instructor. The role, method and elements related to mindfulness are describes in this Mindfulness Diploma Course. Moreover, you will know about mindfulness meditation and empirical evidence in this Mindfulness Diploma Course. With the help of Mindfulness Diploma Course you can explore mindfulness meditation. Enrolling in this Mindfulness Diploma Course provides learners with all the skills they need to make a positive influence in their personal and professional lives. Main Course: Mindfulness Course Special Offers of this Mindfulness: Mindfulness Course This Mindfulness: Mindfulness Course includes a FREE PDF Certificate. Lifetime access to this Mindfulness: Mindfulness Course Instant access to this Mindfulness: Mindfulness Course Get FREE Tutor Support to this Mindfulness: Mindfulness Course Mindfulness: Mindfulness Our "Mindfulness" course is the ideal choice for you if you're looking for a life-changing experience that will improve your general wellbeing. You can recover control and find peace in the middle of the storm with the aid of the Mindfulness: Mindfulness course. With the help of our extensive Mindfulness: Mindfulness course, which delves deeply into the practice of mindfulness, you will gain the skills, strategies, and resources required to make positive changes in your life. Who is this course for? Mindfulness: Mindfulness Without any prior experience, anyone can enrol on this Mindfulness Diploma Course. Requirements Mindfulness: Mindfulness To enrol in this Mindfulness: Mindfulness Course, students must fulfil the following requirements. To join in our Mindfulness: Mindfulness Course, you must have a strong command of the English language. To successfully complete our Mindfulness: Mindfulness Course, you must be vivacious and self driven. To complete our Mindfulness: Mindfulness Course, you must have a basic understanding of computers. A minimum age limit of 15 is required to enrol in this Mindfulness: Mindfulness Course. Career path Mindfulness: Mindfulness Following the completion of the Mindfulness Diploma Course, you will be able to grasp all the information and abilities to develop yourself and your career in the relevant work field.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for those with a basic understanding of Microsoft Windows and who need to learn foundational Word skills, such as creating, editing, and formatting documents; inserting simple tables and creating lists; and employing a variety of techniques for improving the appearance and accuracy of document content. Overview In this course, you will learn fundamental Word skills. You will: Navigate and perform common tasks in Word, such as opening, viewing, editing, saving, and printing documents, and configuring the application. Format text and paragraphs. Perform repetitive operations efficiently using tools such as Find and Replace, Format Painter, and Styles. Enhance lists by sorting, renumbering, and customizing list styles. Create and format tables. Insert graphic objects into a document, including symbols, special characters, illustrations, pictures, and clip art. Format the overall appearance of a page through page borders and colors, watermarks, headers and footers, and page layout. Use Word features to help identify and correct problems with spelling, grammar, readability, and accessibility. These days, most people take electronic word processing for granted. While we may still write out our grocery lists with pen and paper, we expect to use a computer to create the majority of our documents. It's impossible to avoid word-processing software in many areas of the business world. Managers, lawyers, clerks, reporters, and editors rely on this software to do their jobs. Whether you are an executive secretary or a website designer, you'll need to know the ins and outs of electronic word processing.Microsoft© Word is designed to help you move smoothly through the task of creating professional-looking documents. Its rich features and powerful tools can make your work easy, and even fun. In this course, you'll learn how to use Word on the desktop to create and edit simple documents; format documents; add tables and lists; add design elements andlayout options; and proof documents.Note: Most Office users perform the majority of their daily tasks using the desktop version of the Office software, so that is the focus of this training. The course material will alsoenable you to access and effectively utilize many web-based resources provided with your Microsoft 365 subscription. This includes brief coverage of key skills for using Word for theWeb and OneDrive. Helpful notes throughout the material alert you to cases where the online version of the application may function differently from the primary, desktop version.This course may be a useful component in your preparation for the Microsoft Word (Microsoft 365 Apps and Office 2019): Exam MO-100 and Microsoft Word Expert (Microsoft 365 Apps and Office 2019): Exam MO-101 certification exams. Lesson 1: Getting Started with Word Topic A: Navigate in Microsoft Word Topic B: Create and Save Word Documents Topic C: Edit Documents Topic D: Work with Word for the Web Lesson 2: Formatting Text and Paragraphs Topic A: Apply Character Formatting Topic B: Control Paragraph Layout Topic C: Align Text Using Tabs Topic D: Display Text in Bulleted or Numbered Lists Topic E: Apply Borders and Shading Lesson 3: Working More Efficiently Topic A: Make Repetitive Edits Topic B: Apply Repetitive Formatting Topic C: Use Styles to Streamline Repetitive Formatting Tasks Topic D: Customize the Word Environment Lesson 4: Managing Lists Topic A: Sort a List Topic B: Format a List Lesson 5: Adding Tables Topic A: Insert a Table Topic B: Modify a Table Topic C: Format a Table Topic D: Convert Text to a Table Lesson 6: Inserting Graphic Objects Topic A: Insert Symbols and Special Characters Topic B: Add Images to a Document Lesson 7: Controlling Page Appearance Topic A: Apply a Page Border and Color Topic B: Add Headers and Footers Topic C: Control Page Layout Topic D: Add a Waterm Lesson 8: Preparing to Publish a Document Topic A: Check Spelling, Grammar, and Readability Topic B: Preview and Print Documents Topic C: Use Research Tools Topic D: Check Accessibility Topic E: Dictate Text in a Document Topic F: Save a Document to Other Form Additional course details: Nexus Humans Microsoft Word for Office 365 (Desktop or Online) (v1.1) Part 1 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the Microsoft Word for Office 365 (Desktop or Online) (v1.1) Part 1 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 4 Days 24 CPD hours This course is intended for Administrators, architects, and business leaders who manage Nutanix clusters in the datacenter Managers and technical staff seeking information to drive purchase decisions Anyone who is seeking the Nutanix Certified Professional - Multicloud Infrastructure (NCP-MCI) certification Overview During this program, attendees will: Develop a working knowledge of the Nutanix product family. Understand the requirements and considerations involved in setting up a Nutanix cluster. Familiarize themselves with cluster management and monitoring via the Prism web console. Learn how to create, manage, and migrate VMs, set up data protection services, and plan for business continuity. Understand how to plan and handle upgrades, assess future requirements, and create what-if scenarios to adress scaling for business needs. The Nutanix Enterprise Cloud Administration (ECA) course enables administrators (system, network, and storage) to successfully configure and manage Nutanix in the datacenter. The course covers many of the tasks Nutanix administrators perform through the use of graphical user interfaces (GUIs) and command line interfaces (CLIs). It also provides insight into a Nutanix cluster?s failover and self-healing capabilities, offers tips for solving common problems, and provides guidelines for collecting information when interacting with Nutanix Support Introduction The section describes the Nutanix HCI solution, walks you through the components of the Nutanix Enterprise Cloud, and explains the relationship between physical and logical cluster components. Managing the Nutanix Cluster In this section, you will use the Prism console to monitor a cluster, configure a cluster using various interfaces, use the REST API Explorer to manage the cluster, and learn how to deploy Nutanix-specific PowerShell cmdlets. Securing the Nutanix Cluster This section shows how to secure a Nutanix cluster through user authentication, SSL certificate installation, and cluster access control. Acropolils Networking This section explains how to configure managed and unmanaged Acropolis networks and describes the use of Open vSwitch (OVS) in Acropolis. You will learn how to display and manage network details, differentiate between supported OVS bond modes, and gain insight into default network configuration. VM Management This section shows you how to upload images, and how to create and manage virtual machines. Health Monitoring and Alerts In this section, you will use the Health Dashboard to monitor a cluster?s health and performance. You will also use Analysis Dashboard to create charts that you can export with detailed information on a variety of components and metrics. Distributed Storage Fabric This section discusses creating and configuring storage containers, including the storage optimization features: deduplication, compression, and erasure coding. AHV Workload Migration Using Nutanix Move, this section shows how to migrate workloads to a cluster running AHV. This is followed by a lab where a VM running on a Nutanix cluster configured with ESXi is migrated to a Nutanix cluster running AHV. File and Volumes This section gives you detailed information on Nutanix Volumes, which provides highly available, high-performance block storage through a few easy configuration steps. It also discusses Nutanix Files. Understanding Infrastructure Resiliency This section shows how Nutanix provides comprehensive data protection at all levels of the virtual datacenter: logical and physical. Data Protection Data can be replicated between Nutanix clusters, synchronously and asynchronously. This section shows how to configure a Protection Domain (PD) and Remote Sites, recover a VM from a PD, and perform a planned failover of a PD. Prism Central Having discussed and used Prism Element earlier, this section looks at the capabilities of Prism Central. With the added functionality provided by a Pro license, the focus is on features related to monitoring and managing multiple activities across a set of clusters. Monitoring the Nutanix Cluster This section shows you where to locate and how to interpret cluster-related log files. In addition, you will take a closer look at the Nutanix Support Portal and online help. Cluster Management and Expansion This section outlines essential life-cycle operations, including starting/stopping a Nutanix cluster, as well as starting/shutting down a node. You will also learn how to expand a cluster, manage licenses, and upgrade the cluster?s software and firmware. Remote Office Branch Office (ROBO) Deployments In this section, you will understand various configurations and requirements specific to a ROBO site. This includes hardware/software, Witness VM, networking, failure and recovery scenarios for two-node clusters, and the seeding process. Additional course details: Nexus Humans NECA: Nutanix Enterprise Cloud Administration training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the NECA: Nutanix Enterprise Cloud Administration course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is suitable for anyone responsible for configuring, managing or supporting a Veeam Availability Suite v10 environment. Overview After completing this course, attendees should be able to: Describe Veeam Availability Suite components usage scenarios and relevance to their own environment. Effectively manage data availability in on-site, off-site, cloud and hybrid environments. Ensure both Recovery Time Objectives (RTOs) and Recovery Point Objectives (RPOs) are met. Install and configure Veeam Availability Suite into their environment, ensuring data is protected effectively. Adapt with an organization's evolving technical, business and regulatory needs. Ensure recovery is possible, effective, efficient, secure and compliant with business and legal requirements. Provide visibility of the business data assets, and produce effective reports and dashboards to monitor performance and risks. Conduct basic troubleshooting and analysis of their Veeam Availability Suite environment. This three-day, technical deep dive Veeam© Availability Suite? v10: Configuration and Management training course is focused on teaching IT professionals the skills to configure, manage and support a Veeam Availability Suite v10 solution. With extensive hands-on-labs, the class enables administrators and engineers to effectively manage data in an ever-changing technical and business environment, bringing tangible benefit to businesses in the digital world. Introduction Describe RTOs and RPOs, what they mean for your business, how to manage and monitor performance against them The 3-2-1 Rule and its importance in formulating a successful backup strategy Identify key Veeam Availability Suite components and describe their usage scenarios Building Backup Capabilities Backup methods, the appropriate use cases and impact on underlying file systems Create, modify, optimize and delete backup jobs, including NAS Backup jobs. Explore different tools and methods, such as BitLooker? and Deduplication, to maximize environment performance Global Settings and their usage to prevent production performance bottlenecks, encrypt network traffic data and control network jurisdiction Restoring from Backup Identify and describe the different restore tools and their features. Ensure you have the confidence to use the correct restore tool at the right time Using Secure Restore to prevent the restoration of malware Disaster recovery from backup, respond accordingly to a variety of real-world recovery scenarios Backup Copy Jobs Simple vs Advanced Backup Copy Jobs, how to create and modify them using best practices to ensure efficient recovery Utilizing tape jobs, how to create and modify Replication Identify and describe the options available for replication, the use cases and impacts of using Create, modify and delete replication jobs, outline considerations to ensure success Failover Identify and describe in detail, failover features and the appropriate usage Develop, prepare and test failover plans to ensure recovery Disaster recovery from replica, respond accordingly to a variety of real-world recovery scenarios Advanced Repository Capabilities Ensure efficiency by being able to select appropriate transport modes while being aware of the impact of various backup functions on the infrastructure Ensure scalability by integrating off-site S3 storage Ensure compatibility with existing deduplication appliances Testing Backup and Replication Testing backups and replicas to ensure you can recover, what you need, when you need to Configure Veeam DataLabs? and setup sandbox environments based on backup, replicas and storage snapshots Using Veeam DataLabs Staged Restore to manage and comply with General Data Protection Regulation (GDPR) legislation before releasing restores to production Veeam Backup Enterprise Manager Manage multiple Veeam Backup & Replication? installations from a single web console, maintaining a view of your entire virtual environment, ensuring data protection of ROBO and Enterprise environments. Create user and group roles, delegate workloads whilst maintaining data control Enable encryption password loss protection, helping to restore encrypted data in case of lost or forgotten encryption passwords Veeam ONE Monitor your Virtual, Physical and Cloud environments with Veeam ONE? and assess the different views available Configure Veeam ONE for your specific technical and business requirements, describe the alarm options available and how to customize their usage Set up, use and customize Veeam ONE Reporter, creating the reports and dashboards you require technically and for the business Support Locate, migrate or restore backup configuration Identify and locate appropriate support resources Troubleshooting methodology to identify, isolate and remediate support issues Additional course details: Nexus Humans VEEAM-VMCE Availability Suite v10.0: Configuration and Management training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the VEEAM-VMCE Availability Suite v10.0: Configuration and Management course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Guide children’s behaviour with positive techniques in our Children's Social Behaviour Training course.

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