CWISA training course description This CWISA course covers wireless technologies with reference to IoT. It examines from an IoT perspective how wireless works, and is an excellent introduction to IoT for the wireless engineer. Topics range from wireless technologies, RF, to mobile networks, IoT, and security. What will you learn Describe wireless networking and IoT technologies. Explain basic RF communications. Plan wireless solutions. Describe how to implement wireless solutions. Use best practices in implementing wireless solutions. CWISA training course details Who will benefit: Anyone working with IoT technologies. Prerequisites: RF fundamentals. Duration 4 days CWISA training course contents Introduction to wireless technologies History of wireless, radio waves and frequencies, wireless technologies and related components, common components of wireless solutions, LAN networking requirements, Network security, Implementing wireless solutions, staging, documentation, security updates, Industry organizations, IEEE, compatibility and certification groups. Wireless network use cases Wireless BANs, Wireless PANs, Wireless LANs, Wireless MANs, Wireless WANs, Wireless sensor networks, New network driver-Internet of Things, IoT for industry (IIoT), IoT for connected vehicles, Residential environments, Retail, Education (K12), Higher education, Agriculture, Smart cities / Public access, Health care, Office buildings, Hospitality, Industry, Stadiums, arenas, and large public venues. Planning wireless solutions Identifying use cases and applications, common wireless requirements and constraints, performing a wireless system design, selecting and evaluating design parameters. RF communications RF wave characteristics, RF propagation behaviours, RF signal metrics, fundamentals of wireless modulation. other wireless carriers, common frequency bands. Radio frequency hardware Hardware levels, basic RF hardware components (circuit board level), RF link types (use category). RF device types. Mobile communications networks Mobile networks, LTE, 5G, Use cases. Short-range, low-rate, and low-power networks RF and speed, RF and range, RF and power, 802.11, 802.15.4, Bluetooth, LoRa (Long range) / LoRaWAN, ZigBee, 6LoWPAN, NB-IoT and LTE-M. Wireless sensor networks What is a Wireless Sensor Network (WSN)? WSN applications, Sensors and actuators, WSN architectures, Planning a WSN. Internet of Things (IoT) Internet of Things (IoT) defined, IoT history and its definition revisited, one more comment on the definition of IoT, IoT verticals, Oil & Gas, IoT structure/ architecture basics, IoT connected objects. Securing wireless networks Confidentiality, integrity and availability, Privacy, non-repudiation, authenticity & safety, Importance of authentication in wireless networks, Key cryptographic technologies & concepts, Authentication methods, Authorisation, OAuth 2.0 authorisation framework, monitoring. Troubleshooting wireless solutions Proper solutions design, designing and implementing wireless solutions, basic installation procedures, general configuration considerations, troubleshooting and remediation, troubleshoot common problems in wireless solutions. Programming, scripting and automation What is an API? categories of APIs, common API communication methods, choosing a language, why are we integrating systems? Application & integration architectures. Data structures & types, XML, YAML, API types.
Portfolio Management Skills: In-House Training The main purpose of this workshop is to equip and enable people in a portfolio management office and PMO to effectively and efficiently support the Executive Leadership and Operational Management to plan, implement, manage, and evolve portfolio management in their organization. There is a deliberate focus on preparing you to become a strong and effective change advocate for meaningful portfolio management that delivers objective measurements of benefit contribution towards the strategic objectives to lead, manage, and continuously improve portfolio management governance, processes, and frameworks with and through the direction of a portfolio practice, principles, and delivery boards. What you Will Learn At the end of this program, you will be able to: Articulate the benefits of portfolio management Link the initiatives in an organization with its strategic objectives Participate in the introduction of portfolio management in an organization Create or improve the portfolio governance structure Lead the inventory of ongoing and new initiatives Assist the executives in the prioritization of initiatives through the use of Multi-criteria Analysis and other selection tools Support the executives in balancing the portfolio based on the optimal use of resources and priorities Create a portfolio delivery plan Define thresholds and variance reporting criteria Assist the executives and the financial team in the definition of Stage Gate Funding Lead the Stage Gate reviews Analyze the benefits that are being realized by the initiatives Foundation Concepts Definitions Benefits of Portfolio Management Objectives of Portfolio Management Portfolio Life Cycles Governing the Portfolio Portfolio Governance structure Roles and responsibilities Initial activities when starting portfolio management Prioritizing Initiatives Prioritize purpose Multi-Criteria Analysis Analytical Hierarchy Process (AHP) Strategic alignment Balancing the Portfolio Allocating resources and budgets Communicating decisions of initiatives status Planning the Portfolio Planning review cycles Using Stage Gate Funding Setting thresholds and variance reporting Tool examples Managing the Portfolio Delivery Project and Program Life Cycles Stage Gate Reviews Loop back to Prioritize, Balance and Plan Interaction with the Portfolio Delivery Board Project, Program and Functional Managers' roles and responsibilities
The Level 1 Diploma in Motor Vehicle Studies is designed to encourage and enable learners who have an interest in this area of study to acquire knowledge and skills to aid progression to further study or employment.
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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
Get inside my mind as I work out how to paint this magnificent Emu in colourful Vibrant acrylics.
LAN training course description A concise overview course covering Local Area Networks with particular emphasis on the use of Ethernet and Wireless LANS. As well as explaining buzzwords we cover how the technology works at a simple level. After defining LANs the course moves onto Ethernet and switching also covering VLANs. WiFi is then covered, with coverage of 802.11 standards and frequencies along with integrating WiFi with Ethernet. The course then covers routers and their role in connecting networks and the course finishes with a comparison of Ethernet vs WiFi and when to use them. What will you learn Describe how Ethernet works (in simple terms) and when to use Ethernet. Explain the difference between a switch and a router. Describe how WiFi works (in simple terms). Describe the role of Access points. Evaluate wireless technologies and when to use them. List the speeds of various LAN technologies. LAN training course details Who will benefit: Sales staff, managers and other non technical staff. Prerequisites: None. Duration 1 day LAN training course contents LANS What is a LAN? LAN standards, LAN choices, choosing the media, copper, UTP, cat5e, fibre, RF, bandwidth speeds, link aggregation, Full/half duplex. Ethernet What is Ethernet? 802.3, parts of Ethernet, Ethernet evolution, MAC addresses, frames, broadcasts. Ethernet switches What are switches, switches versus hubs, how switches work, ways to configure switches, Loops, STP. VLANs What are VLANs? Why have VLANs, impact of VLANs, Tagging (aka trunking), 802.1Q Wireless LANS Type of wireless LAN, RF frequencies, 2.4GHz, 5GHz, others, interference, standards, 802.11 and variants, CSMA/CA. Wireless LANS NICs, Access points, integration with Ethernet, multiple access points, mesh networks, WiFi security. Interconnecting LANs Routers, connecting networks, interconnecting VLANs, IP addressing, Layer 3 switches. Summary WiFi vs Ethernet.
Definitive Segment Routing course description This Segment Routing (SR) training course is a comprehensive program designed to equip network professionals with the knowledge and skills needed to implement and manage SR in modern networking environments. Segment Routing is a cutting-edge network architecture that enhances network flexibility, scalability, and efficiency. This course offers in-depth coverage of SR principles, protocols, and practical implementation techniques. Hands on sessions are used to reinforce the theory rather than teach specific manufacturer equipment. What will you learn Explain packet paths when implementing SLB. Explain how Segment Routing works. Explain the relationship between SR and MPLS. Use SR for Traffic Engineering. Troubleshoot Segment Routing. Implement TI-LFA using Segment Routing Definitive Segment Routing course details Who will benefit: This course is ideal for network engineers, architects, and administrators who want to stay up-to-date with the latest networking technologies and enhance their expertise in Segment Routing. Prerequisites: Concise MPLS for engineers Duration 3 days Definitive Segment Routing course contents Introduction to Segment Routing (SR) What is SR? Source based routing, SPRING, history, segments, why SR? SR benefits.SR usage: Traffic Engineering, Shortest path, local protection. Relationship between SR and MPLS, SRv6. Hands on Investigating the base network. Segment Routing architecture SR domains, SR paths, SR segments. Segment types. Segment IDs, combining segments, IGP extensions, control plane components. Hands on Configuring SR, exploring how SR works, Segment Routing protocols SR-MPLS. MPLS label stack operations. Segment Routing Global Block (SRGB). SRLB. IS-IS and OSPF extensions for SR. Prefix segments, adjacency segments. SRGB/IGP interactions. Multidomain SR policies. SPF, Strict SPF. Hands on Analysing IGP SR extension operation. Investigating the SRGB. Segment Routing Traffic Engineering RSVP-TE versus SR-TE. SR policies. Anycast and binding SIDs. SR flexible algorithm flex-algo, Performance measurement delay. Hands on Optimising network paths for various applications. SR integration with 'older' technologies MPLS and LDP integration with SR. Hands on Integration. Topology Independent Loop Free Alternative Classic LFA and IP/MPLS protection mechanisms. TI-LFA protection options. Hands on TI-LFA operation with SR and LDP traffic. Scenarios SDN. Managing SR with SR controllers. Analyse, optimise, automate. Network slicing. BGP peering segments Path Computation Elements, BGP Link State. BGP prefix segments, BGP peer segments. Egress peer engineering. SR enabled VPNs. Hands onBGP segment routing. Troubleshooting Segment Routing IP toolkit: ping and traceroute. MPLS toolkit: MPLS ping, MPLS echo request/reply, MPLS ping, MPLS traceroute and path discovery. Router show commands. Hands on Used throughout the course during exercises. SRv6 Note this is an optional extra day. See our one day SRv6 course for details. IPv6 headers review, routing headers, IPv6 segment, SRv6 segment Identifiers. IPv6 Segment Routing Header. SRH procedures. Hands on Configuring SRv6, Analysing SRv6 operation.
The Level 1 Certificate in Motor Vehicle Studies is designed to encourage and enable learners who have an interest in this area of study to acquire knowledge and skills to aid progression to further study or employment.