7771 Mode courses delivered Online

Network virtualization training course description This course covers network virtualization. It has been designed to enable network engineers to recognise and handle the requirements of networking Virtual Machines. Both internal and external network virtualization is covered along with the technologies used to map overlay networks on to the physical infrastructure. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer implementations. What will you learn Evaluate network virtualization implementations and technologies. Connect Virtual Machines with virtual switches. Explain how overlay networks operate. Describe the technologies in overlay networks. Network virtualization training course details Who will benefit: Engineers networking virtual machines. Prerequisites: Introduction to virtualization. Duration 2 days Network virtualization training course contents Virtualization review Hypervisors, VMs, containers, migration issues, Data Centre network design. TOR and spine switches. VM IP addressing and MAC addresses. Hands on VM network configuration Network virtualization What is network virtualization, internal virtual networks, external virtual networks. Wireless network virtualization: spectrum, infrastructure, air interface. Implementations: Open vSwitch, NSX, Cisco, others. Hands on VM communication over the network. Single host network virtualization NICs, vNICs, resource allocation, vSwitches, tables, packet walks. vRouters. Hands on vSwitch configuration, MAC and ARP tables. Container networks Single host, network modes: Bridge, host, container, none. Hands on Docker networking. Multi host network virtualization Access control, path isolation, controllers, overlay networks. L2 extensions. NSX manager. OpenStack neutron. Packet walks. Distributed logical firewalls. Load balancing. Hands on Creating, configuring and using a distributed vSwitch. Mapping virtual to physical networks VXLAN, VTEP, VXLAN encapsulation, controllers, multicasts and VXLAN. VRF lite, GRE, MPLS VPN, 802.1x. Hands on VXLAN configuration. Orchestration vCenter, vagrant, OpenStack, Kubernetes, scheduling, service discovery, load balancing, plugins, CNI, Kubernetes architecture. Hands on Kubernetes networking. Summary Performance, NFV, automation. Monitoring in virtual networks.

Total SIPp course description SIPp is a robust performance testing tool designed for evaluating the SIP protocol. This comprehensive course takes you on a journey from the initial installation of SIPp to mastering fundamental scenarios, exploring diverse architectures, delving into statistics analysis, and crafting XML scenario files. What will you learn Monitor SIP traffic with SIPp. Use SIPp for performance testing. Use the standard SIPp scenarios. Create custom scenarios in XML for SIPp. Total SIPp course details Who will benefit: Those working with SIP. Prerequisites: Definitive SIP for engineers Duration 2 days Total SIPp course contents Introduction What is SIPp? SIP review: UAC, UAS, INVITE, BYE. Sample SIP call flows. Hands on Wireshark, SIP call flow. Installing SIPp Getting SIPp, installing SIPp. Using SIPp Running sipp. sipp with uas scenario, sipp with uac scenario. The integrated scenarios. Online help. Hands on uac, uas. Controlling SIPp Hot keys, commands, UDP socket. Running SIPp in the background. Traffic control. SIPp performance testing. Hands on Changing call rates, remote control, pausing traffic. Monitoring SIP traffic Scenario screen, statistics. Response times, counters. Hands on Monitoring SIP traffic. More integrated scenarios SIPp and media and RTP. 3PCC. 3PCC extended. Transport modes: UDP, TCP, TLS, SCTP, IPv6 mono and multi socket. Hands on Third Party Call Control. XML What is XML? Content, markup, elements, attributes. Start tags, end tags. Hands on Displaying embedded scenarios, looking at the XML files of the integrated scenarios. Creating your own XML scenarios scenario, message commands, send, recv, nop, pause, sendCmd, recvCmd, common sipp scenario attributes, command specific sipp scenario attributes. XML DTD, jEdit. Hands on uac and uas scenario XML files. Recv actions Log and warning, exec, variables, variable types, variable scope. External variables. Hands on RTP streaming, Change a calls network destination, injection files. Regular expressions What is an RE. POSIX 1003.2. Re injection. Validation. Hands on regex example.

Advanced Ethernet switching training course description An advanced hands on switching course for those already familiar with the basics such as STP and VLANs. The course starts with advanced diagnostics and network monitoring moving onto switch protocols. A large part of the second day is spent implementing QoS and security such as 802.1x. What will you learn Troubleshoot switching. Explain how a number of switch protocols work, including: UDLD LLDP LACP DTP VTP/MVRP Design redundancy into switched networks. Implement QoS on switches. Harden switches. Advanced Ethernet switching training course details Who will benefit: Technical staff working with Ethernet switches. Prerequisites: None Duration 2 days Advanced Ethernet switching training course contents Switches Switch review, troubleshooting, diagnostics, L2 traceroute, UDLD, message logging, Wireshark, port mirroring, Hands on: Troubleshooting. Network management SNMP, SNMPv3, RMON, Netflow, Sflow. System logging. Hands on: Managing switches with SNMP. Syslogd. Switches and automatic configuration Auto-MDIX, LLDP, CDP, Link aggregation, LACP, Link state tracking, VLANS and tags, DTP. Hands on: Discovery, dynamic configuration. RSTP 802.1w, new port roles and states, new BPDUs, rapid convergence, topology changes, compatibility issues. L3 redundancy, VRRP, GLBP. Design issues. Hands on: RSTP, VRRP. VLANS: Registration protocols Why VTP? VTP modes, how VTP works, VTP pruning. GVRP, MVRP. Hands on: Dynamic VLANs STP variations and alternatives 802.1s (multiple spanning tree), regions, rings, L2MP, TRILL. Hands on: 802.1s Multicasting What is multicasting, Static configuration, IGMP snooping, CGMP, MVR. IPv6 MLD snooping. Hands on: Multicast through switches QoS Storm control, DSCP, 802.1Q, 802.1p, mapping, classification, policy, Ingress queues, Egress queues. Dropping frames, limiting bandwidth. Hands on: Voice through switches. More VLANS Native VLANs, Voice VLANs Security Static MAC addresses, AAA, RADIUS, Port based authentication, 802.1x, Guest VLANs, L2 attacks, SSH, HTTPS. Hands on: Hardening switches. Miscellaneous NTP, managing the MAC address table, managing system resources, SDN

HTTP streaming training course description This course looks at the delivery of video streams using HTTP adaptive streaming. Both MPEG DASH and HLS are investigated. Hands on sessions primarily involve using Wireshark to analyse streams. What will you learn Use Wireshark to analyse and troubleshoot HTTP video streams. Explain HTTP adaptive streaming works. Evaluate and compare MPEG DASH and HLS. Use tools to create HTTP adaptive streams. HTTP streaming training course details Who will benefit: Anyone working in the broadcast industry. Prerequisites: TCP/IP foundation for engineers Duration 2 days HTTP streaming training course contents What is HTTP streaming? The old way. Progressive downloads versus streaming. Why not UDP and RTP for delivery? Adaptive bit rate streaming. Standards. Hands on Base network setup. Using WireShark for HTTP streams. HTTP protocol stack IP, TCP, IPv6. HTTP. HTTP 1.0, HTTP 1.1, HTTP 2.0, HTTP header fields. HTML 5. Hands on Analysing HTTP. Adaptive bitrate streaming principles Chunks, fragments, segments. Manifest files. Encoding, resolution, bitrates. Addressing, relative and absolute URLs, redirection. When does the client switch streams? Switch points. Hands on Walk through of client behaviours on a stream. HTTP streaming architecture Server components, distribution components, client software. CDN, caching, multiple servers. Hands on Analysing CDN and Internet delivery. TCP and HTTP streaming interactions TCP ACK, TCP connections, unicast only. TCP flow control, TCP and performance. Hands on TCP window sizes. MPEG DASH Stakeholders, DASH architecture and model, codec agnostic, XML, Media Presentation Description, Media Presentation, segment formats. Hands on MPEG DASH analysis. HTTP Live Streaming and others Stakeholders. Media segments, media playlists, master playlists. Adobe HTTP dynamic streaming, Microsoft smooth streaming. Hands on Analysing HLS. Tools mp4dash, mp4fragment, libdash. Apple developer tools for HLS. Hands on Creating segmented content. Security HTTPS, encryption, content protection. Hands on Encryption analysis. Summary Choosing a streaming method. Impact of live versus VoD. Web sockets.

Definitive Puppet training course description Puppet is a framework and toolset for configuration management. This course covers Puppet to enable delegates to manage configurations. Hands on sessions follow all the major sections. What will you learn Deploy Puppet. Manage configurations with Puppet. Build hosts with Puppet. Produce reports with Puppet. Definitive Puppet training course details Who will benefit: Anyone working with Puppet. Prerequisites: Linux fundamentals. Duration 2 days Definitive Puppet training course contents Getting started with Puppet What is Puppet, Selecting the right version of Puppet, Installing Puppet, Configuring Puppet. Developing and deploying Puppet The puppet apply command and modes of operation, Foreground Puppet master, Developing Puppet with Vagrant, Environments, Making changes to the development environment, Testing the new environments with the Puppet agent, Environment branching and merging, Dynamic Puppet environments with Git branches, Summary, Resources. Scaling Puppet Identifying the challenges, Running the Puppet master with Apache and Passenger, Testing the Puppet master in Apache, Load balancing multiple Puppet masters, Scaling further, Load balancing alternatives. Measuring performance, Splay time, Summary, Going further, Resources. Externalizing Puppet configuration External node classification, Storing node configuration in LDAP, Summary, Resources. Exporting and storing configuration Virtual resources, Getting started with exported and stored configurations, Using exported resources, Expiring state resources, Summary, Resources. Puppet consoles The foreman, Puppet enterprise console, Puppetboard, Summary, Resources. Tools and integration Puppet forge and the module tool, Searching and installing a module from the forge, Generating a module, Managing module dependencies, Testing the modules, Developing Puppet modules with Geppetto, Summary, Resources. Reporting with Puppet Getting started, Configuring reporting, Report processors, Custom reporting, Other Puppet reporters, Summary, Resources. Extending Facter and Puppet Writing and distributing custom facts, Developing custom types, providers and functions, Summary, Resources, Complex data structures, Additional backends, Hiera functions in depth, Module data bindings, Hiera examples. Jiera-2, Summary, Resources. Mcollective Installing and configuring Mcollective, testing, Mcollective plugins, accessing hosts with Metadata. Hiera Lists, initial Hiera configuration, Hiera command line utility, complex data structures, additional backends, Hiera functions in depth, module data bindings. Hiera-2.

OTT TV for engineers course description This course covers OTT TV by primarily looking at the delivery of video streams using HTTP adaptive streaming. Both MPEG DASH and HLS are investigated. Hands on sessions involve using Wireshark to analyse streams as well as crafting segmented content. What will you learn Explain what OTT TV is, and how it works. Describe the OTT TV architecture. Use Wireshark to analyse and troubleshoot OTT video streams. Explain how HTTP adaptive streaming works. Evaluate and compare MPEG DASH and HLS. Use tools to create OTT TV adaptive streams. OTT TV for engineers course details Who will benefit: Anyone working in the broadcast industry. Prerequisites: TCP/IP foundation for engineers. Duration 2 days OTT TV for engineers course contents What is OTT TV? Brodeo providers vs ISPs. Progressive downloads versus streaming. Why not UDP and RTP for delivery? Adaptive bit rate streaming. Standards. Hands on: Base network setup. Using WireShark for HTTP streams. HTTP protocol stack IP, TCP, IPv6. HTTP. HTTP 1.0, HTTP 1.1, HTTP 2.0, HTTP header fields. HTML 5. Hands on: Analysing HTTP. Adaptive bitrate streaming principles Chunks, fragments, segments. Manifest files. Encoding, resolution, bitrates. Addressing, relative and absolute URLs, redirection. When does the client switch streams? Switch points. Hands on: Walk through of client behaviours on a stream. OTT TV streaming architecture Server components, distribution components, client software. CDN, caching, multiple servers. Hands on: Analysing CDN and Internet delivery. TCP and HTTP streaming interactions TCP ACK, TCP connections, unicast only. TCP flow control, TCP and performance. Hands on: TCP window sizes. MPEG DASH Stakeholders, DASH architecture and model, codec agnostic, XML, Media Presentation Description, Media Presentation, segment formats. Hands on: MPEG DASH analysis. HTTP Live Streaming and others Stakeholders. Media segments, media playlists, master playlists. Adobe HTTP dynamic streaming, Microsoft smooth streaming. Hands on: Analysing HLS. Tools mp4dash, mp4fragment, libdash. Apple developer tools for HLS. Hands on: Creating segmented content. Security HTTPS, encryption, content protection. Hands on: Encryption analysis. Summary Choosing a streaming method. Impact of live versus VoD. Web sockets.

Duration 4 Days 24 CPD hours This course is intended for Software engineers concerned with building, managing and deploying AI solutions that leverage Azure AI Services, Azure AI Search, and Azure OpenAI. They are familiar with C# or Python and have knowledge on using REST-based APIs to build computer vision, language analysis, knowledge mining, intelligent search, and generative AI solutions on Azure. AI-102 Designing and Implementing an Azure AI Solution is intended for software developers wanting to build AI infused applications that leverage?Azure AI Services,?Azure AI Search, and?Azure OpenAI. The course will use C# or Python as the programming language. Prerequisites Before attending this course, students must have: Knowledge of Microsoft Azure and ability to navigate the Azure portal Knowledge of either C# or Python Familiarity with JSON and REST programming semantics Recommended course prerequisites AI-900T00: Microsoft Azure AI Fundamentals course 1 - Prepare to develop AI solutions on Azure Define artificial intelligence Understand AI-related terms Understand considerations for AI Engineers Understand considerations for responsible AI Understand capabilities of Azure Machine Learning Understand capabilities of Azure AI Services Understand capabilities of the Azure Bot Service Understand capabilities of Azure Cognitive Search 2 - Create and consume Azure AI services Provision an Azure AI services resource Identify endpoints and keys Use a REST API Use an SDK 3 - Secure Azure AI services Consider authentication Implement network security 4 - Monitor Azure AI services Monitor cost Create alerts View metrics Manage diagnostic logging 5 - Deploy Azure AI services in containers Understand containers Use Azure AI services containers 6 - Analyze images Provision an Azure AI Vision resource Analyze an image Generate a smart-cropped thumbnail 7 - Classify images Provision Azure resources for Azure AI Custom Vision Understand image classification Train an image classifier 8 - Detect, analyze, and recognize faces Identify options for face detection analysis and identification Understand considerations for face analysis Detect faces with the Azure AI Vision service Understand capabilities of the face service Compare and match detected faces Implement facial recognition 9 - Read Text in images and documents with the Azure AI Vision Service Explore Azure AI Vision options for reading text Use the Read API 10 - Analyze video Understand Azure Video Indexer capabilities Extract custom insights Use Video Analyzer widgets and APIs 11 - Analyze text with Azure AI Language Provision an Azure AI Language resource Detect language Extract key phrases Analyze sentiment Extract entities Extract linked entities 12 - Build a question answering solution Understand question answering Compare question answering to Azure AI Language understanding Create a knowledge base Implement multi-turn conversation Test and publish a knowledge base Use a knowledge base Improve question answering performance 13 - Build a conversational language understanding model Understand prebuilt capabilities of the Azure AI Language service Understand resources for building a conversational language understanding model Define intents, utterances, and entities Use patterns to differentiate similar utterances Use pre-built entity components Train, test, publish, and review a conversational language understanding model 14 - Create a custom text classification solution Understand types of classification projects Understand how to build text classification projects 15 - Create a custom named entity extraction solution Understand custom named entity recognition Label your data Train and evaluate your model 16 - Translate text with Azure AI Translator service Provision an Azure AI Translator resource Specify translation options Define custom translations 17 - Create speech-enabled apps with Azure AI services Provision an Azure resource for speech Use the Azure AI Speech to Text API Use the text to speech API Configure audio format and voices Use Speech Synthesis Markup Language 18 - Translate speech with the Azure AI Speech service Provision an Azure resource for speech translation Translate speech to text Synthesize translations 19 - Create an Azure AI Search solution Manage capacity Understand search components Understand the indexing process Search an index Apply filtering and sorting Enhance the index 20 - Create a custom skill for Azure AI Search Create a custom skill Add a custom skill to a skillset 21 - Create a knowledge store with Azure AI Search Define projections Define a knowledge store 22 - Plan an Azure AI Document Intelligence solution Understand AI Document Intelligence Plan Azure AI Document Intelligence resources Choose a model type 23 - Use prebuilt Azure AI Document Intelligence models Understand prebuilt models Use the General Document, Read, and Layout models Use financial, ID, and tax models 24 - Extract data from forms with Azure Document Intelligence What is Azure Document Intelligence? Get started with Azure Document Intelligence Train custom models Use Azure Document Intelligence models Use the Azure Document Intelligence Studio 25 - Get started with Azure OpenAI Service Access Azure OpenAI Service Use Azure OpenAI Studio Explore types of generative AI models Deploy generative AI models Use prompts to get completions from models Test models in Azure OpenAI Studio's playgrounds 26 - Build natural language solutions with Azure OpenAI Service Integrate Azure OpenAI into your app Use Azure OpenAI REST API Use Azure OpenAI SDK 27 - Apply prompt engineering with Azure OpenAI Service Understand prompt engineering Write more effective prompts Provide context to improve accuracy 28 - Generate code with Azure OpenAI Service Construct code from natural language Complete code and assist the development process Fix bugs and improve your code 29 - Generate images with Azure OpenAI Service What is DALL-E? Explore DALL-E in Azure OpenAI Studio Use the Azure OpenAI REST API to consume DALL-E models 30 - Use your own data with Azure OpenAI Service Understand how to use your own data Add your own data source Chat with your model using your own data 31 - Fundamentals of Responsible Generative AI Plan a responsible generative AI solution Identify potential harms Measure potential harms Mitigate potential harms Operate a responsible generative AI solution

Introduction to Virtualization course description A comprehensive tour of virtualization. The course concentrates on the actual technologies involved as opposed to any one vendor solution. What will you learn Explain the concepts of virtualization. Partition servers. Create Virtual Machines. Introduction to Virtualization course details Who will benefit: Anyone looking for an introduction to Virtualization. Prerequisites: None. Duration 2 days Introduction to Virtualization course contents Virtualization Concepts What is Virtualisation? What are virtual machines (VMs)? Virtualisation Landscape. Network Virtualisation. Suitability for Organisations. Advantages of deploying Virtualisation. Downsides of deploying Virtualisation. Overview of Virtualisation products. Hypervisors What is a hypervisor? Difference between type 1 and 2 hypervisors. Available hypervisors. Hypervisors and device drivers. Hands on: Installing Oracle VirtualBox on Windows. Creating/Importing/Configuring VMs. Virtualization Hosts Hardware and resource requirements. Installation of the hypervisor. Hands on: Installing Hyper-V role into Windows Server. Creating/Importing/Configuring VMs. Virtual Machines Creating virtual machines. Resource requirements. Settings. Installation of the guest OS. Additional tools/ extensions for hypervisor integration. VM files and their uses. Virtual hard disk and their formats. Hardware pass through. Hands on: Connecting to VMWare ESXi via WebGUI and using ESXi to create/import/configure VMs. VM Snapshots/Checkpoints What is a snapshot? How to use them and how they impact performance? Creating/deleting/merging of snapshots. Hands on: Using ESXi to create/manage snapshots. Command Line use on the Hypervisor Interacting with the hypervisor through the command line. Simple commands to configure the hypervisor and VMs. Simple scripts. Hands on: Connecting to VMWare ESXi via PowerCLI to manipulate VMs and snaphshots. Virtualization Storage Different types of storage: local vs remote. Local and remote storage technologies. Configuring storage. Hands on: Using ESXi to deploy VMs on remote NFS storage. Virtual Networking How is networking done in virtualization environments. What is a virtual switch and vNIC and what are their performance characteristics? NIC teaming and trunking in the virtual world. Port groups and isolation. Physical NICs and their use in virtual switches. Hands on: Using ESXi to create and configure vswitches and networking. Templates and clones What is a template? What is a clone? When to use templates and clones to optimize VM deployment. Migrating/Importing VMs What is migration? Migrating compute and storage. Importing VMs from files or physical machines. Hands on: Using VMWare vCenter Server to clone/ template/migrate VMs, tag resources, create local user accounts and assign permissions. VMs and Backups Taking backups of your VMs. Restoring your VMs from backups. Virtualization and Licensing Different licensing models and costs. Containerization Concepts What is a container and how is it different from a virtual machine. When to use containers. Docker and Kubernetes

The NCSP® Foundation accredited (APMG International), certified (NCSC/GCHQ-UK) and recognized (DHS-CISA-USA) certification course introduces business, technology, auditing, and management professionals to the fundamentals of digital business, its risks, and the NIST Cybersecurity Framework's role in helping organizations manage and mitigate digital risk. This course also introduces candidates to an Affordable, Pragmatic, and Scalable Digital Value Management System (DVMS) Create, Protect, and Deliver (CPD) model designed to enable any size organization to quickly adopt and adapt the frameworks and models (NIST-CSF, NIST Privacy Framework, CMMC, etc.) that may be required to address internal, external (regulatory) and cyber threat landscape changes. The DVMS enables enterprises to become adaptive, cyber-resilient organizations capable of creating, protecting, and delivering trusted digital business value to their stakeholders.

Game design training face to face training customised and bespoke.