40 Courses in Cardiff delivered Live Online

Duration 4 Days 24 CPD hours This course is intended for Candidates should be familiar with Dynamics 365 Customer Insights and have firsthand experience with one or more additional Dynamics 365 apps, Power Query, Microsoft Dataverse, Common Data Model, and Microsoft Power Platform. They should also have working knowledge of practices related to privacy, compliance, consent, security, responsible AI, and data retention policy. Overview After completing this course, you will be able to: Clean, transform, and ingest data into Dynamics 365 Customer Insights Create a unified customer profile Work with Dynamics 365 Audience insights Enrich data and predictions Set up and manage external connections Administer and monitor Customer Insights Customer Data Platform specialists implement solutions that provide insight into customer profiles and that track engagement activities to help improve customer experiences and increase customer retention. In this course, students will learn about the Dynamics 365 Customer Insights solution, including how to unify customer data with prebuilt connectors, predict customer intent with rich segmentation, and maintain control of customer data. This specialty course starts with creating a unified profile and then working with customer data. Module 1: Get started with Dynamics 365 Customer Insights Introduction to the customer data platform Administer Dynamics 365 Customer Insights Explore user permissions in Dynamics 365 Customer Insights Module 2: Ingest data into Dynamics 365 Customer Insights Import and transform data Connect to data sources Work with data Module 3: Create a unified customer profile in Dynamics 365 Customer Insights Map data Match data Merge data Find customers Module 4: Work with Dynamics 365 Customer Insights Explore Audience insights Define relationships and activities Work with measures Work with segments Module 5: Enrich data and predictions with Audience insights Enrich data Use predictions Use machine learning models Module 6: Manage external connections with Customer Data Platform Export Customer Insights data Use Customer Insights with Microsoft Power Platform Display Customer Insights data in Dynamics 365 apps More ways to extend Customer Insights

Duration 2 Days 12 CPD hours This course is intended for Enterprise Network System Installers System Integrators System Administrators Network Administrators Solutions Designers Overview Upon completion of this course, you will be able to: Identify the various components and architecture of the Cisco SD-WAN solution. Deploy vEdge routers in a secure extensible network. Create templates to aide in the deployment and operation of the secure extensible network. Configure and verify overlay routing in the secure extensible network. Create simple policies to control traffic flow in the secure extensible network. The Cisco SD WAN Operation and Deployment (SDWFND) v1.0 is a 2-day, instructor-led, hands-on course that addresses the Cisco SD-WAN Operations and Deployment functions. Cisco SD-WAN is a new technology, this training covers salient features such as zero-touch provisioning, secure network bring-up, configuration using feature templates, configuration of Overlay Management Protocol (OMP) and policies for network traffic management. Module 1: SD-WAN Solution Components Lesson 1: SD-WAN Solution Overview Lesson 2: SD-WAN Components Lesson 3: Managing SD-WAN Components Module 2: Secure Extensible Network Deployment Lesson 1: Secure Control Plane Operation Lesson 2: Secure Control Plane Deployment Lesson 3: Secure Data Plane Operation Lesson 4: Cloud Deployments and Redundancy Module 3: SD-WAN Template Deployment Lesson 1: Templates Overview Lesson 2: Feature Templates Lesson 3: Device Templates Lesson 4: Attaching Devices to Templates Module 4: SD-WAN Overlay Routing Lesson 1: Overlay Routing Overview Lesson 2: OMP Route Advertisements Lesson 3: OMP Route Redistribution and Network Segmentation Lesson 4: Configuring and Verifying Overlay Routing Module 5: SD-WAN Policies and QoS Lesson 1: Policy Overview and Framework Lesson 2: vSmart Policy Operation and Construction Lesson 3: Forwarding and QoS Overview Lesson 4: Configuring and Monitoring QoS Forwarding Lab outline Lab 1: Manage and Monitor SD-WAN Components Lab 2: Deploy and Verify SD-WAN vEdge Routers Lab 3: Deploy SD-WAN Templates Lab 4: SD-WAN Overlay Routing Lab 5: SD-WAN Policies

Duration 5 Days 30 CPD hours This course is intended for Built for IT Professionals with extensive networking and Citrix ADC experience. This course is built for IT Professionals who are responsible for defining the overall structure or architecture of a Citrix networking environment. This course encompasses advanced Citrix networking configurations and leading Citrix design principles. Overview How to identify and prioritize business drivers, constraints, and requirements using the Citrix Consulting methodology Assess environment requirements and learn to apply leading design principles to address them in a multi-site Citrix ADC deployment Apply advanced authentication and load balancing principles In this expert level 5-day training course you will be exposed to advanced networking and Citrix ADC concepts and configurations. Through lecture, lab exercises, and real-world case studies, you will learn to look critically at environment requirements, constraints, and business drivers to create a complex Citrix networking solution. Topics to be covered in this course include multi-site and multitenant deployments, advanced authentication and load balancing, and automation and orchestration and advanced troubleshooting. This training will also prepare you for the Citrix Certified Expert in Networking (CCE-N) exam. Module 1: Networking Methodology and Assessment Understanding the Citrix methodology Business Drivers and Requirementrs User Segmentation Application Assessment Capabilities Assessment Module 2: Citrix Networking Deployment Architecture and Topology Multi-Site Deployments Multi Tennant Infrastructure Cloud Deployments High Availability Citrix ADC Double-Hop Scenarios Secure Web Gateway Module 3: Advanced Authentication and Authorization Authorization Policies Access Policies Advanced Authentication Options Multi-Factor Authentication nFactor Authentication AAA Session Management Module 4: Citrix ADC Security Authorization Pre-authentication and Endpoint Analysis Scans Protection against Layer 4-7 Attacks Web App Firewall Module 5: Citrix Gateway Configuration Considerations ICA Proxy Configuration VPN Access Clientless Access Split Tunneling RDP Proxy Deployment and Configuration Module 6: Advanced Load Distribution and Link Load balancing Advanced Load Balancing Advanced Load Balancing Link Load Balancing Firewall Load Balancing Microsoft Exchange Load Balancing Advanced Global Server Load Balancing Global Server Load Balancing Persistence DNS, Policies, Expressions, Actions, and Views GSLB Monitoring and Considerations Module 7: Application Delivery Management Automation and Orchestration Application Delivery Management Outbound Traffic Dashboard Automation Orchestration Configuration Jobs Configuration Audit NITRO API StyleBooks (Net-new)

Duration 2 Days 12 CPD hours This course is intended for Enterprise Network System Installers System Integrators System Administrators Network Administrators Solutions Designers Overview Upon completion of this course, you will be able to: Identify the various components and architecture of the Cisco SD-WAN solution. Deploy vEdge routers in a secure extensible network. Create templates to aide in the deployment and operation of the secure extensible network. Configure and verify overlay routing in the secure extensible network. Create simple policies to control traffic flow in the secure extensible network. The Cisco SD-WAN Operation and Deployment (ENSDW) v1.0 course provides an overview of the Cisco SD-WAN solution and SD-WAN components. Students will learn how to create, manage, and operate a secure extensible network using Cisco SD-WAN products. The course covers how to configure, operate, and monitor overlay routing in a secure extensible network. Students will also learn about policies and quality of service (QoS) in the SD-WAN overlay network. SD-WAN Solution Components SD-WAN Solution Overview SD-WAN Components Managing SD-WAN Components Secure Extensible Network Deployment Secure Control Plane Operation Secure Control Plane Deployment Secure Data Plane Operation Cloud Deployments and Redundancy SD-WAN Template Deployment Templates Overview Feature Templates Device Templates Attaching Devices to Templates SD-WAN Overlay Routing Overlay Routing Overview OMP Route Advertisements OMP Route Redistribution and Network Segmentation Configuring and Verifying Overlay Routing SD-WAN Policies and QoS Policy Overview and Framework vSmart Policy Operation and Construction Forwarding and QoS Overview Configuring and Monitoring QoS Forwarding Additional course details: Nexus Humans ENSDW-Cisco SD-WAN Operation and Deployment 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 ENSDW-Cisco SD-WAN Operation and Deployment 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.

Arm yourself with a robust research toolkit that will help you uncover deep behavioural insights on user needs and motivations so you can design better experiences.

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

The need for key staff to have commercial skills is paramount, as the public sector is increasingly opened up as a commercial market, in which organisations compete against each other and the private sector for contracts. Generating additional income and being commercially aware is vital for this to be a success, and is what many public sector organisations are looking to do. This programme will help you: See commercial awareness as not just another skill-set, but as a different mind-set Use a variety of tried-and-tested commercial, analytical decision-making techniques and tools Define your commercial objectives Develop a strategic focus Start looking at service clients as market segments Analyse, in a competitive context, your service offering Plan a commercial strategy, prepare for its implementation and see it through to execution 1 What is commercial thinking? Understand what it means to be a commercial thinker Identifying commercial opportunities often involves not only a different skill set but also a different mindset; looking at the services that you provide 2 Defining strategic commercial objectives Defining your key commercial objectives Prioritising your strategic objectives Two key strategic planning tools:Resource and Competency MatrixPESTLE How to apply these tools to your particular situation 3 Developing a strategic focus Decision-making on how to compete in the markets identified by your strategic objectives requires a strategic focus Developing strategic focus A tool for helping you to make those decisions: using the Ansoff Matrix 4 Defining customer targets How to think more commercially by understanding who all your customers are and how they differ from each other how to apply the principles to your areas to identify the type of customers you have and their key characteristics - Customer segmentation Who are your customers? How do their needs vary? - Scenarios 5 The competitive market place Understanding the competitive forces at play Different types of competition Analysing your competitive environment using Porter's 5 Forces model 6 Meeting stakeholder expectations Two simple models to help you identify the key stakeholders who could influence your commercial environment How to use your stakeholders to help you achieve your commercial objectives 7 Implementation - systems, structures and processes Effective commercial activity involves working with others to implement ideas and strategies What do you need to have in place before you implement your commercial strategy? How to health-check your organisation prior to implementation using the McKinsey 7S framework 8 Implementation - people and culture A good commercial strategy only works if the people involved buy in to the ideas and if the culture of the organisation is conducive to the effective implementation How the latest thinking in behavioural economics can help you develop your culture and people to work commercially 9 Tools and checklists Be more commercial within your sphere of influence using a commercial checklist to help you Using the checklist as a benchmark against the most commercially aware organisations Using the checklist as a health check - both corporately and individually

Duration 5 Days 30 CPD hours This course is intended for Developed for IT Professionals with extensive networking and Citrix ADC experience. This course is built for IT Professionals who are responsible for defining the overall structure or architecture of a Citrix networking environment. This course encompasses advanced Citrix networking configurations and leading Citrix design principles. Overview How to identify and prioritize business drivers, constraints, and requirements using the Citrix Consulting methodologyAssess environment requirements and learn to apply leading design principles to address them in a multi-site Citrix ADC deploymentApply advanced authentication and load balancing principles In this expert training course students will be exposed to advanced networking and Citrix ADC concepts and configurations. Through lecture, lab exercises, and real-world case studies, students will learn to look critically at environment requirements, constraints, and business drivers to create a complex Citrix networking solution. Topics to be covered in this course include multi-site and multitenant deployments, advanced authentication and load balancing, and automation and orchestration and advanced troubleshooting. This training will also prepare students for the Citrix Certified Expert in Networking (CCE-N) exam.This course includes a voucher to take the related exam (1Y0-440: Citrix Networking Assessment, Design, and Advanced Configuration) and earn your Citrix Certified Expert ? Networking (CCE-N) certification. Networking Methodology and Assessment Understanding the Citrix methodology Business Drivers and Requirements User Segmentation Application Assessment Capabilities Assessment Citrix Networking Deployment Architecture and Topology Multi-Site Deployments Multi Tennant Infrastructure Cloud Deployments High Availability Citrix ADC Double-Hop Scenarios Secure Web Gateway Advanced Authentication and Authorization Authorization Policies Access Policies Advanced Authentication Options Multi-Factor Authentication nFactor Authentication AAA Session Management Citrix ADC Security Authorization Pre-authentication and Endpoint Analysis Scans Protection against Layer 4-7 Attacks Web App Firewall Citrix Gateway Configuration Considerations ICA Proxy Configuration VPN Access Clientless Access Split Tunneling RDP Proxy Deployment and Configuration Advanced Load Distribution and Link Load balancing Advanced Load Balancing Link Load Balancing Firewall Load Balancing Microsoft Exchange Load Balancing Advanced Global Server Load Balancing Global Server Load Balancing Persistence DNS, Policies, Expressions, Actions, and Views GSLB Monitoring and Considerations Application Delivery Management Automation and Orchestration Application Delivery Management Outbound Traffic Dashboard Automation Orchestration Configuration Jobs Configuration Audit NITRO API StyleBooks (Net-new) Additional course details: Nexus Humans CNS-420 Citrix Networking Assessment, Design, and Advanced Configuration 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 CNS-420 Citrix Networking Assessment, Design, and Advanced Configuration 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 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