2835 DOM courses delivered Online

Duration 5 Days 30 CPD hours This course is intended for Channel partners and resellers Network administrators Network engineers Sales engineers System engineers Technical architects Technical support personnel Overview After taking this course, you should be able to: Identify the Cisco Digital Network Architecture solution by describing the vision, strategy, general concepts, and components. Describe the Cisco DNA Center design application, hierarchical network design, and basic network settings, and describe the integration of Cisco DNA Center with Cisco Identity Services Engine (Cisco ISE) for Automation and Assurance. Describe the Cisco DNA Center Inventory and the available mechanisms for discovering and adding network devices, and explore the device compatibility with Cisco DNA Center and SD-Access. Describe the Cisco DNA Center automation features such as configuration templates, software image maintenance, and Plug and Play (PnP) device onboarding. Explore the Cisco DNA Center user interface, the available workflows for onboarding devices, and how to design and manage a network. Introduce Cisco SD-Access, describe the different node types in the fabric and the two-level segmentation provided by the solution, and take a deep dive into the control and data plane protocols used in Cisco SD-Access. Describe the Cisco DNA Center workflow for deploying Cisco SD-Access, defining all the prerequisite network settings and profiles, defining the required policies, creating fabric domains and sites, and provisioning fabric nodes. Create and manage fabric domains and sites, provision fabric devices, and onboard your endpoints in a single site or distributed fabric campus network. Describe the features available for automating and monitoring wireless networks with Cisco DNA Center, and describe the available deployment models with their benefits and limitations, such as wireless Over-the-Top (OTT) and SD-Access Wireless. Describe the Cisco SD-Access Extension for IoT solution, its architecture and components, and the benefits and limitations of the solution Describe the use cases and migration scenarios for migrating users from traditional campus to SD The Transforming to a Cisco Intent-Based Network (IBNTRN) v1.1 course teaches you how the functionality of Cisco© SD-Access fits into Cisco Digital Network Architecture (Cisco DNA?). Through a combination of lessons and hands-on learning, you will practice operating, managing, and integrating Cisco DNA Center, programmable network infrastructure, and Cisco SD-Access fundamentals. You will learn how Cisco delivers intent-based networking across the campus, branch, WAN, and extended enterprise and ensures that your network is operating as intended. Course Outline Introducing Cisco DNA Architecture Cisco DNA Center Design Cisco DNA Center Inventory Cisco DNA Center Automation Explore Cisco DNA Center and Automating Network Changes Introducing Cisco Software-Defined Access Deploying Cisco Software-Defined Access Deploy Wired Fabric Networks with Cisco DNA Center Cisco SD-Access for Wireless Cisco SD-Access Extension for IoT Deploy Brownfield and Fabric Wireless Network with Cisco DNA Center Migrating to Cisco SD-Access Cisco SD-Access Multicast Integrating Cisco DNA Center Deploy SD-Access Layer 2 Borders and Multicast and Integrate Cisco DNA Center with External Services or Applications Understanding Programmable Network Infrastructure Operating and Managing Cisco DNA Infrastructure Test Drive Cisco DNA Center APIs

Duration 5 Days 30 CPD hours This course is intended for Linux Professional Institute Certification (LPIC-2) 202 training is suitable for individuals with roles of: System administrator Network administrator Technician DevOps Overview Upon successful completion of this course, students will be able to: configure BIND to function as an authoritative and as a recursive, caching-only DNS server install and configure a web server install and configure a proxy server, including access policies, authentication and resource usage set up a Samba server for various clients configure a DHCP server configure PAM to support authentication using various available methods perform queries and updates to an LDAP server configure a basic OpenLDAP server including knowledge of LDIF format and essential access controls manage an e-mail server, including the configuration of e-mail aliases, e-mail quotas and virtual e-mail domains configure an FTP server for anonymous downloads and uploads receive security alerts from various sources, install, configure and run intrusion detection systems and apply security patches and bugfixes configure a VPN (Virtual Private Network) and create secure point-to-point or site-to-site connections. This course prepares students to take the 202 exam of the LPI level 2 certification. To gain LPIC-2 certification, an individual should have an active LPIC-1 certification. Domain Name Server Basic DNS server configuration Create and maintain DNS zones Securing a DNS server HTTP Services Basic Apache configuration Apache configuration for HTTPS Implementing Squid as a caching proxy Implementing Nginx as a web server and a reverse proxy File Sharing Samba Server Configuration NFS Server Configuration Network Client Management DHCP configuration PAM authentication LDAP client usage Configuring an OpenLDAP server E-Mail Services Using e-mail servers Managing E-Mail Delivery Managing Mailbox Access System Security Configuring a router Managing FTP servers Secure shell (SSH) Security tasks OpenVPN Additional course details: Nexus Humans Linux Professional Institute Certification (LPIC-2) 202 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 Linux Professional Institute Certification (LPIC-2) 202 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 2 Days 12 CPD hours This course is intended for The primary audience for this course is as follows:Anyone interested in knowing about DNA Center and SD-AccessPersonnel involved in SD-Access Design and ImplementationNetwork Operations team with SD-Access solutionNetwork admin staff that deal with User AccessChannel Partner SEs and other sales supportNetwork Access Control administrationNetwork AdministratorsNetwork ArchitectsNetwork Engineers Overview Upon completing this course, the learner will be able to meet these overall objectives:Know and understand Cisco?s SD-Access concepts, features, benefits, terminology and the way this approach innovates common administrative tasks on today?s networks.Differentiate and explain each of the building blocks of SD-Access SolutionExplain the concept of ?Fabric? and the different node types that conform it (Fabric Edge Nodes, Control Plane Nodes, Border Nodes)Describe the role of LISP in Control Plane and VXLAN in Data Plane for SD-Access SolutionUnderstand the role of DNA Center as solution orchestrator and Intelligent GUIBe familiar with workflow approach in DNA Center and its 4 Steps: Design, Policy, Provision and Assurance DNA Center and SD-Access offer Cisco?s next-generation programmable digital network to help automate common network access security features and streamline the redundant, complex configuration required to allow different groups of users access to the network infrastructure. This network security training course allows network administrators to quickly allow differentiated access for end users on the network while allowing the network to react automatically to day zero and other types of attacks. Introduction to Cisco?s Software Defined Access (SD-Access) SD-Access Overview SD-Access Benefits SD-Access Key Concepts SD-Access Main Components SD-Access Campus Fabric The concept of Fabric Node types Fabric Edge Nodes Control Plane Nodes Border Nodes LISP as protocol for Control Plane VXLAN as protocol for Data Plane Concept of Virtual Network Fabric-enabled WLAN DNA Center and Workflow for SD-Access Introduction to DNA Center Workflow for SD-Access in DNA Center Integration with Cisco ISE for Policy Enforcement Integration with Cisco NDP for Analytics and Assurance Relationship with APIC-EM controller DNA Center Workflow First Step - Design Creating Enterprise and Sites Hierarchy Discuss and Demonstrate General Network Settings Loading maps into the GUI IP Address Administration Administering Software Images Network Device Profiles DNA Center Workflow Second Step - Policy 2-level Hierarchy Policy Types ISE Integration with DNA Center Cross Domain Policies DNA Center Workflow Third Step - Provision Devices Onboarding Fabric Domains Adding Nodes DNA Center Workflow Fourth Step ? Assurance Introduction to Analytics NDP Fundamentals Overview of DNA Assurance Components of DNA Assurance DNA Center Assurance Dashboard Implementing WLAN in SD-Access Solution WLAN Integration Strategies in SD-Access Fabric SD-Access Wireless Architecture Sample Design for SD-Access Wireless Campus Fabric External Connectivity for SD-Access Enterprise Sample Topology for SD-Access Role of Border Nodes Types of Border Nodes Single Border vs. Multiple Border Designs Collocated Border and Control Plane Nodes Distributed (separated) Border and Control Plane Nodes

Duration 3.5 Days 21 CPD hours This course is intended for This course is for AWS Cloud Architects with expertise in designing and implementing solutions running on AWS who now want to design for Microsoft Azure. Overview After completing this course, students will be able to: Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects who have previously designed for Amazon Web Services how to translate business requirements into secure, scalable, and reliable solutions for Azure. Introduction to Azure Subscriptions and accounts Resource groups and templates in Azure Resource Manager Azure global infrastructure Azure regions Azure Availability Zones Comparison with AWS Implement Azure Active Directory Introduction to Azure Active Directory Domains and custom domains Safety features Guest users in Azure Active Directory Manage multiple directories Comparison with AWS Implement and manage hybrid identities Introduction to Azure AD Connect Comparison with AWS Implement virtual networking Azure Virtual Network and VNet peering VPN and ExpressRoute connections Comparison with AWS Implement VMs for Windows and Linux Configure high availability Comparison with AWS Implement load balancing and network security Implement Azure Load Balancer Implement an Azure Application Gateway Implement Azure Firewall Implement network security groups and application security groups Comparison with AWS Implement container-based applications Configure Azure Kubernetes Service Publish a solution on an Azure Container Instance Comparison with AWS Implement an application infrastructure Create an App Service plan Create and configure Azure App Service Configure networking for an App Service Introduction to Logic Apps and Azure Functions Comparison with AWS Implement storage accounts Azure Storage core concepts Managing the Azure Blob storage lifecycle Working with Azure Blob storage Comparison with AWS Implement NoSQL databases Introduction to Azure Cosmos DB Consistency Select appropriate CosmosDB APIs Set up replicas in CosmosDB Comparison with AWS DynamoDB Implement Azure SQL databases Configure Azure SQL database settings Implement Azure SQL Database managed instances Configure high availability for an Azure SQL database Comparison with AWS Implement cloud infrastructure monitoring Monitor security Monitor cost Configure a Log Analytics workspace Comparison with AWS Implement and manage Azure governance solutions Assign RBAC roles Configure management access to Azure Implement and configure an Azure Policy Comparison with AWS Manage security for applications Implement Azure Key Vault Implement and configure Azure AD Managed Identities Register and manage applications in Azure AD Comparison with AWS Migration, backup, and disaster recovery management Migrate workloads Implement Azure Backup for VMs Implement disaster recovery Comparison with AWS

Duration 5 Days 30 CPD hours This course is intended for Ideal candidates include network professionals who are looking to build their foundational knowledge of the ClearPass product portfolio. Overview After you successfully complete this course, expect to be able to: Ability to setup ClearPass as a AAA server Demonstrate Configuration Guest, OnGurad, Onboard and Profiling features Integrate with External AD Server Understand Monitoring and Reporting Demonstrate Scaling and deployment of best practices Configure AAA services for both wired and wireless networks Demonstrate the configuration of Aruba Downloadable User Roles. Demonstrate the configuration of Dynamic Segmentation with Aruba switches. This course prepares participants with foundational skills in Network Access Control using the ClearPass product portfolio. This 5-day classroom session includes both instructional modules and labs to teach participants about the major features of the ClearPass portfolio. Participants will learn how to setup ClearPass as an AAA server, and configure the Policy Manager, Guest, OnGuard and Onboard feature sets. In addition, this course covers integration with external Active Directory servers, Monitoring and Reporting, as well as deployment best practices. The student will gain insight into configuring authentication with ClearPass on both wired and wireless networks. Intro to ClearPass BYOD High Level Overview Posture and Profiling Guest and Onboard ClearPass for AAA Policy Service Rules Authentication Authorization and Roles Enforcement Policy and Profiles Authentication and Security Concepts Authentication Types Servers Radius COA Active Directory Certificates Intro to NAD NAD Devices Adding NAD to ClearPass Network Device Groups Network Device Attributes Aruba Controller as NAD Aruba Switch Aruba Instant Monitoring and Troubleshooting Monitoring Troubleshooting Logging Policy Simulation ClearPass Insight Insight Dashboard Insight Reports Insight Alerts Insight Search Insight Administration Insight Replication Active Directory Adding AD as Auth Source Joining AD domain Using AD services External Authentication Multiple AD domains LDAP Static Host Lists SQL Database External Radius Server Guest Guest Account creation Web Login pages Guest Service configuration Self-registration pages Configuring NADS for Guest Guest Manager Deep Dive Web Login Deep Dive Sponsor Approval MAC Caching Onboard Intro to Onboard Basic Onboard Setup Onboard Deepdive Single SSID Onboarding Dual SSID Onboarding Profiling Intro to Profiling Endpoint Analysis Deep Dive Posture Intro to Posture Posture Deployment Options OnGuard Agent Health Collection OnGuard workflow 802.1x with Posture using Persistent/dissolvable agent OnGuard web Login Monitoring and Updates Operation and Admin Users Operations Admin Users Clustering and Redundancy Clustering Redundancy LAB Licensing ClearPass Licensing Base License Applications ClearPass Exchange Intro Examples General HTTP Palo Alto Firewall Configuration Case Study Objectives Discussion Advanced Labs Overview Wired Port Authentication 802.1X for access layer switch ports Profiling on Wired Network Configuration of Dynamic Segmentation Aruba Downloadable User Roles Downloadable User Role Enforcement in ClearPass Aruba Controller/Gateway configuration Aruba Switch configuration Troubleshooting

Duration 3 Days 18 CPD hours This course is intended for This course is geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

Duration 3 Days 18 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brandnew version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative dversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 4 Days 24 CPD hours This course is intended for This course is geared for attendees with Intermediate IT skills who wish to learn Computer Vision with tensor flow 2 Overview This 'skills-centric' course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Working in a hands-on learning environment, led by our Computer Vision expert instructor, students will learn about and explore how to Build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Run your models on mobile devices and web pages and improve their performance. Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Computer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. Hands-On Computervision with TensorFlow 2 is a hands-on course that thoroughly explores TensorFlow 2, the brand-new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. This course begins with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the course demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. Computer Vision and Neural Networks Computer Vision and Neural Networks Technical requirements Computer vision in the wild A brief history of computer vision Getting started with neural networks TensorFlow Basics and Training a Model TensorFlow Basics and Training a Model Technical requirements Getting started with TensorFlow 2 and Keras TensorFlow 2 and Keras in detail The TensorFlow ecosystem Modern Neural Networks Modern Neural Networks Technical requirements Discovering convolutional neural networks Refining the training process Influential Classification Tools Influential Classification Tools Technical requirements Understanding advanced CNN architectures Leveraging transfer learning Object Detection Models Object Detection Models Technical requirements Introducing object detection A fast object detection algorithm ? YOLO Faster R-CNN ? a powerful object detection model Enhancing and Segmenting Images Enhancing and Segmenting Images Technical requirements Transforming images with encoders-decoders Understanding semantic segmentation Training on Complex and Scarce Datasets Training on Complex and Scarce Datasets Technical requirements Efficient data serving How to deal with data scarcity Video and Recurrent Neural Networks Video and Recurrent Neural Networks Technical requirements Introducing RNNs Classifying videos Optimizing Models and Deploying on Mobile Devices Optimizing Models and Deploying on Mobile Devices Technical requirements Optimizing computational and disk footprints On-device machine learning Example app ? recognizing facial expressions

Duration 5 Days 30 CPD hours This course is intended for This course is for IT Professionals with expertise in designing and implementing solutions running on Microsoft Azure. They should have broad knowledge of IT operations, including networking, virtualization, identity, security, business continuity, disaster recovery, data platform, budgeting, and governance. Azure Solution Architects use the Azure Portal and as they become more adept they use the Command Line Interface. Candidates must have expert-level skills in Azure administration and have experience with Azure development processes and DevOps processes. Overview Secure identities with Azure Active Directory and users and groups. Implement identity solutions spanning on-premises and cloud-based capabilities Apply monitoring solutions for collecting, combining, and analyzing data from different sources. Manage subscriptions, accounts, Azure policies, and Role-Based Access Control. Administer Azure using the Resource Manager, Azure portal, Cloud Shell, and CLI. Configure intersite connectivity solutions like VNet Peering, and virtual network gateways. Administer Azure App Service, Azure Container Instances, and Kubernetes. This course teaches Solutions Architects how to translate business requirements into secure, scalable, and reliable solutions. Lessons include virtualization, automation, networking, storage, identity, security, data platform, and application infrastructure. This course outlines how decisions in each theses area affects an overall solution. Implement Azure Active Directory Overview of Azure Active Directory Users and Groups Domains and Custom Domains Azure AD Identity Protection Implement Conditional Access Configure Fraud Alerts for MFA Implement Bypass Options Configure Guest Users in Azure AD Configure Trusted IPs Manage Multiple Directories Implement and Manage Hybrid Identities Install and Configure Azure AD Connect Configure Password Sync and Password Writeback Configure Azure AD Connect Health Implement Virtual Networking Virtual Network Peering Implement VNet Peering Implement VMs for Windows and Linux Select Virtual Machine Size Configure High Availability Implement Azure Dedicated Hosts Deploy and Configure Scale Sets Configure Azure Disk Encryption Implement Load Balancing and Network Security Implement Azure Load Balancer Implement an Application Gateway Understand Web Application Firewall Implement Azure Firewall Implement Azure Front Door Implementing Azure Traffic Manager Implement Storage Accounts Storage Accounts Blob Storage Storage Security Managing Storage Accessing Blobs and Queues using AAD Implement NoSQL Databases Configure Storage Account Tables Select Appropriate CosmosDB APIs Implement Azure SQL Databases Configure Azure SQL Database Settings Implement Azure SQL Database Managed Instances High-Availability and Azure SQL Database In this module, you will learn how to Create an Azure SQL Database (single database) Create an Azure SQL Database Managed Instance Recommend high-availability architectural models used in Azure SQL Database Automate Deployment and Configuration of Resources Azure Resource Manager Templates Save a Template for a VM Evaluate Location of New Resources Configure a Virtual Hard Disk Template Deploy from a template Create and Execute an Automation Runbook Implement and Manage Azure Governance Create Management Groups, Subscriptions, and Resource Groups Overview of Role-Based Access Control (RBAC) Role-Based Access Control (RBAC) Roles Azure AD Access Reviews Implement and Configure an Azure Policy Azure Blueprints Manage Security for Applications Azure Key Vault Azure Managed Identity Manage Workloads in Azure Migrate Workloads using Azure Migrate VMware - Agentless Migration VMware - Agent-Based Migration Implement Azure Backup Azure to Azure Site Recovery Implement Azure Update Management Implement Container-Based Applications Azure Container Instances Configure Azure Kubernetes Service Implement an Application Infrastructure Create and Configure Azure App Service Create an App Service Web App for Containers Create and Configure an App Service Plan Configure Networking for an App Service Create and Manage Deployment Slots Implement Logic Apps Implement Azure Functions Implement Cloud Infrastructure Monitoring Azure Infrastructure Security Monitoring Azure Monitor Azure Workbooks Azure Alerts Log Analytics Network Watcher Azure Service Health Monitor Azure Costs Azure Application Insights Unified Monitoring in Azure

Duration 3 Days 18 CPD hours This course is intended for This course is recommended for administrators and engineers. Overview What you'll learn: Understand the differences between Citrix Virtual Apps and Desktops 2203 LTSR on-premises and the Citrix DaaS. Install, configure, and manage Citrix Cloud Connectors. Create Citrix DaaS workloads. Deliver app and desktop resources to users. Migrate existing on-premises Citrix Virtual Apps and Desktops 2203 LTSR infrastructure to Citrix Cloud. In this course you will learn how to create a new Citrix DaaS deployment and how to migrate to Citrix DaaS from an on-premises Citrix Virtual Apps and Desktops Site. Get hands-on as the course guides you through the architecture, communications, management, installation, and configuration of Citrix DaaS on Citrix Cloud and resource locations that the host apps and desktops for your users. This course is a necessary step in enabling you with the right training and skills, to not only understand, manage, and deliver successfully, but also to make well-informed planning decisions along the way. Module 1: Introduction to Citrix DaaS New Citrix Workspace Packaging Citrix Virtual Apps and Desktops - On- Premises Site What is Citrix Cloud? Why Citrix DaaS? What is a Migration from Citrix Virtual Apps and Desktops to Citrix DaaS? Citrix Cloud Administration Module 2: Planning - Citrix DaaS Architecture, Security, and Operations Architecture and Deployment Options Citrix DaaS Security Citrix DaaS Operations Module 3: Planning - Citrix Cloud Connectors Cloud Connector Architecture Cloud Connector Services and Communications Overview Cloud Connector Operations in a Resource Location Cloud Connector Resiliency Installing, Updating, and Removing Cloud Connectors Supported Domain Scenarios for Cloud Connectors Securing Cloud Connector Communications Local Host Cache (LHC) Citrix Cloud Connector vs Delivery Controller Operations Module 4: Planning - Citrix DaaS Resource Locations Citrix DaaS Resource Locations Citrix DaaS Hosting Connections Zones Module 5: Active Directory, Authentication, and Authorization Active Directory Design Options Desktops from Non-Domain Joined VDAs Citrix Federated Authentication Service and Identity Provider Services Module 6: Planning - Provisioning VDA Workloads and Delivering Resources Master Images Machine Creation Services (MCS) in Citrix DaaS Citrix Provisioning in Citrix DaaS Machine Catalogs Delivery Groups Citrix Cloud Library Module 7: Planning - Provisioning VDA Workloads and Delivering Resources Selecting Between Citrix digital workspace experience and StoreFront Citrix StoreFront and Citrix digital workspace experience Communications Selecting Between Citrix Gateway Service and On-Premises Citrix Gateway Access Layer Communications User Authentication Module 8: Planning - Citrix DaaS Administration Citrix Cloud Manage and Monitor Delegated Administration Citrix DaaS Remote PowerShell Software Development Kit Manage Multiple Resource Locations Module 9: Planning - Public Cloud Considerations General Public Cloud Considerations Using Autoscale to Power Manage Machines in a Public Cloud Microsoft Azure as a Citrix DaaS Resource Location Amazon Web Services as a Citrix DaaS Resource Location Google Cloud as a Citrix DaaS Resource Location Module 10: Planning - Migrating to Citrix DaaS from Citrix Virtual Apps and Desktops Citrix Cloud Migration Options and Considerations Citrix Automated Configuration Tool Citrix Image Portability Service Module 11: Manage - Operations and Support in Citrix Cloud Citrix Cloud Connector Support Updating and Rolling Back Machine Catalogs VDA Restore Citrix Self-Help Strategy Monitor Your Environment Additional course details: Nexus Humans CWS-250 Citrix DaaS Deployment and 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 CWS-250 Citrix DaaS Deployment and 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.