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ITIL 5 Foundation Training The ITIL® 5 Foundation with exam voucher training is the training that gets you up to speed with the newest version of the world’s most widely used framework for IT service management. You learn how digital products and services can be set up to deliver measurable value to customers and other stakeholders, and how to make IT service delivery and product development better reflect the needs of the people who rely on them. The focus is on value creation, collaboration and continual improvement, so the framework works for you in daily practice, not just on paper. This course helps you understand ITIL 5 and apply it in your own role, whatever that role looks like within your organization. You finish with the knowledge you need to sit the official ITIL 5 Foundation exam. Who is this training for? This training suits anyone who works with or around digital products and services and wants a solid, shared vocabulary for service management: IT professionals, service managers, product owners, team leads and business stakeholders alike. No specific job title or IT background is required, which makes it just as useful for people starting out in service management as for experienced professionals who want to formalize what they already do in practice. Because ITIL 5 is built to apply across an entire organization, it’s also relevant if you work outside a classic IT department but collaborate closely with one. Not sure if this training is the right fit for you? Feel free to get in touch with us. What will you learn? You explain how value and co-creation of value work in digital product and service management You recognize the four dimensions of product and service management: organizations and people, value streams and processes, information and technology, and partners and suppliers You apply the ITIL service value system: guiding principles, governance, value chains and continual improvement You map the ITIL product and service lifecycle: discover, design, acquire, build, transition, operate, deliver and support You analyze and manage value streams within digital organizations You use ITIL concepts to improve service quality, service relationships and customer journeys You prepare for and take the official ITIL (version 5) Foundation exam Prerequisites No prior knowledge is required for this training. It’s designed as a genuine starting point, so whether you’re new to service management or bring years of hands-on experience, you’ll be able to follow along. Not sure if your background is sufficient? Get in touch with us via contact or call us on 020 820 83 62. Practical information Duration: 2 days Price: € 1,795 (excl. VAT) Language: English Course material: You receive digital English-language course material. Delivery method: Classroom at our location, hybrid online, or tailored in-company. Exam Voucher After completing this training, you can sit the official ITIL (version 5) Foundation exam, certified by PeopleCert, the licensed exam authority behind ITIL. An exam voucher is included in this training, so you don’t need to book or pay for the exam separately. Passing the exam earns you the internationally recognized ITIL (version 5) Foundation certificate, the entry point for further ITIL certification paths such as Practice Manager, Managing Professional and Strategic Leader. This training prepares you for two official exams. Exam vouchers for both are included and valid for 12 months, so you’ll need to schedule your exams within that period. ITIL® 5 Managing Professional Transition – Product, Service, Experience Duration: 120 minutes 60 multiple-choice questions Open book exam Pass mark: 70% ITIL® 5 Transformation Duration: 90 minutes 40 multiple-choice questions Open book exam Pass mark: 70% Why SignOn for this training? There are plenty of ICT training providers in the Netherlands. Yet organizations and professionals choose SignOn time and again. There are concrete reasons for that. Practice-driven expert trainer-consultants: Only certified experts (such as MCTs) with at least ten years of hands-on experience. Personal attention: Learning in small groups with plenty of room for your specific learning goals and short lines of communication, even after the training ends. Our own learning approach: Always up-to-date, in-house course materials combined with a strong blended learning methodology. Long-term aftercare: Direct support from your trainer-consultant for practical questions, up to a year after the training. The result of this approach is measurable: with more than 1,500 evaluations we score an average of 9.3, and we’re proud to be Cedeo-certified. Exclusive aftercare: we’re here for you even after the training After the training you can still ask our trainers and consultants your questions. Through our unique aftercare service you get a response almost immediately, by phone or by email. That way you get the most out of what you’ve learned and can put it straight into practice. Follow-up training Once you’re ready for the next step in your ITIL certification path, you can choose between Practice Manager, Managing Professional and Strategic Leader, depending on whether you want to specialize in specific practices, focus on operational service management, or move into strategic leadership. Check our ITIL training range to see which follow-up modules are currently available. Course program Module 1: Introduction Development of IT service management What ITIL is and what ITIL 5 is used for ITIL as a framework for digital product and service management Benefits of ITIL for organizations and professionals Module 2: The four dimensions of product and service management Organizations and people Value streams and processes Information and technology Partners and suppliers Module 3: Key concepts of digital product and service management The service economy Service value Outcomes, costs and risks Digital products and digital services Service relationships and roles Service journey Service quality and service agreements Module 4: The ITIL product and service lifecycle Overview of the lifecycle and related activities Discover, design, acquire, build, transition, operate, deliver, support Module 5: The ITIL service value system Purpose and structure of the ITIL service value system ITIL guiding principles Governance Value chains Management practices Continual improvement and the continual improvement model Module 6: Identifying, mapping and managing value streams Why value streams are important Value streams in digital organizations Value stream analysis Managing value streams Module 7: Next steps Improving organizations with ITIL Professional development ITIL in relation to other frameworks Delivery formats Choose a delivery format that suits you best. The following delivery formats are available for this course: Online hybrid training A trainer provides the training live in the classroom. You follow this training online (from home or office). You have direct contact with the trainer and other participants who participate physically in class or online. Classroom live A face-to-face training on a location in the Netherlands. Employees from different companies are present during this classroom training. Fully catered for, including an extensive lunch. Virtual classroom Attend a the virtual classroom course from any location (workplace or home). You learn from a live instructor and are in contact with other participants. The instructor has the possibility to look at your screen (if necessary) to answer all your questions. This training will take place via Microsoft Teams (free of use). In-company course Our in-company training is tailored to your company. The specialized trainer only deals with what is important for your company and work situation. That makes our tailor-made training very effective. We provide these training courses in Dutch, English and German. The choice for an in-company training provides an attractive discount. Depending on the number of participants, the discount can be as much as 50% compared to participation in an open training. More information or request a quote. Cedeo Recognition: What Does It Mean for You? Cedeo is a household name when it comes to education. There are approximately 300 Cedeo-recognized institutes in the Netherlands. By choosing a Cedeo-approved supplier, you can therefore be sure that you are choosing one of the better education institutes. SignOn and the UWV SignOn ICT Training+ is a recognized training partner of the UWV. SignOn ICT Training+ is one of the few ICT educational organizations recognized by the UWV to provide training to help people return to the labor process.

Bouw complete data-oplossingen met Microsoft Fabric Werk je al met Power BI en wil je de stap maken naar Microsoft Fabric? In deze praktijkgerichte tweedaagse training leer je hoe je jouw Power BI-kennis uitbreidt naar een complete analytics-oplossing. Je werkt met OneLake, Lakehouses, Dataflows Gen2, Data Pipelines, semantic models en Direct Lake. Je bouwt tijdens de training stap voor stap een oplossing van databron tot interactief Power BI-rapport. Voor wie? Deze training is geschikt voor: Power BI developers BI-consultants Data-analisten Analytics engineers Power BI-beheerders Professionals die Power BI-oplossingen willen uitbreiden of migreren naar Microsoft Fabric Wat leer je? Na deze training kun je: uitleggen hoe Microsoft Fabric en Power BI samenwerken; een Fabric-workspace inrichten; bepalen wanneer je een Lakehouse of Data Warehouse gebruikt; gegevens laden en transformeren met Dataflows Gen2; data verwerken en automatiseren met Data Pipelines; een stermodel opbouwen met feiten- en dimensietabellen; een semantic model maken op Fabric-data; werken met Direct Lake, Import en DirectQuery; DAX-measures, relaties en hiërarchieën toevoegen; row-level security instellen; Power BI-rapporten bouwen op een gedeeld semantic model; content uitrollen via deployment pipelines; refreshes, pipelines en capaciteit monitoren; veelvoorkomende performanceproblemen herkennen en oplossen. Programma Dag 1 – Data verzamelen en voorbereiden Introductie tot Microsoft Fabric De relatie tussen Fabric en Power BI Werken met workspaces en Fabric-items OneLake, Lakehouse en Data Warehouse Data laden met Dataflows Gen2 Data verwerken met Data Pipelines Werken met Bronze-, Silver- en Gold-lagen Monitoring van dataflows en pipelines Dag 2 – Modellen, rapporten en beheer Dimensioneel modelleren in Fabric Een stermodel bouwen Semantic models maken Direct Lake, Import en DirectQuery vergelijken DAX-measures en relaties toevoegen Row-level security instellen Power BI-rapporten bouwen Werken met deployment pipelines Monitoring Hub en Capacity Metrics App Performanceproblemen analyseren Praktijk Tijdens de training bouw je een complete analytics-oplossing voor een fictieve retailorganisatie. Je gaat onder andere: brondata inladen; data opschonen en transformeren; een Lakehouse inrichten; een Data Pipeline maken; een stermodel opbouwen; een Direct Lake semantic model maken; een Power BI-rapport ontwikkelen; beveiliging instellen; de oplossing uitrollen; capaciteit en prestaties monitoren. Voorkennis Voor deze training heb je ervaring nodig met: Power BI Desktop; Power Query; datamodellering; DAX; publiceren naar de Power BI-service. Ervaring met SQL is handig, maar niet verplicht. Ervaring met Spark, notebooks of Lakehouses is niet nodig. Trainingsvorm De training bestaat uit korte uitleg, demonstraties en veel praktische oefeningen. Je werkt gedurende beide dagen aan één doorlopende case. Duur 2 dagen Niveau Gemiddeld Resultaat Na afloop kun je zelfstandig een eenvoudige end-to-end Microsoft Fabric-oplossing ontwerpen, bouwen, beveiligen, publiceren en monitoren. Je begrijpt bovendien hoe je bestaande Power BI-oplossingen kunt doorontwikkelen naar een schaalbare Fabric-architectuur. Inclusief Digitaal cursusmateriaal Stapsgewijze labs Voorbeelddata Power Query-, SQL- en DAX-voorbeelden Architectuurvoorbeelden Checklist voor deployment Checklist voor monitoring en troubleshooting Samenvatting Maak de stap van Power BI developer naar Microsoft Fabric analytics developer. Bouw in twee dagen een complete oplossing met OneLake, Dataflows Gen2, Data Pipelines, een semantic model, Direct Lake en Power BI. Werk je al met Power BI en wil je de stap maken naar Microsoft Fabric? In deze praktijkgerichte tweedaagse training leer je hoe je jouw Power BI-kennis uitbreidt naar een complete analytics-oplossing. Je werkt met OneLake, Lakehouses, Dataflows Gen2, Data Pipelines, semantic models en Direct Lake. Je bouwt tijdens de training stap voor stap een oplossing van databron tot interactief Power BI-rapport. Voor wie? Deze training is geschikt voor: Power BI developers BI-consultants Data-analisten Analytics engineers Power BI-beheerders Professionals die Power BI-oplossingen willen uitbreiden of migreren naar Microsoft Fabric Wat leer je? Na deze training kun je: uitleggen hoe Microsoft Fabric en Power BI samenwerken; een Fabric-workspace inrichten; bepalen wanneer je een Lakehouse of Data Warehouse gebruikt; gegevens laden en transformeren met Dataflows Gen2; data verwerken en automatiseren met Data Pipelines; een stermodel opbouwen met feiten- en dimensietabellen; een semantic model maken op Fabric-data; werken met Direct Lake, Import en DirectQuery; DAX-measures, relaties en hiërarchieën toevoegen; row-level security instellen; Power BI-rapporten bouwen op een gedeeld semantic model; content uitrollen via deployment pipelines; refreshes, pipelines en capaciteit monitoren; veelvoorkomende performanceproblemen herkennen en oplossen. Programma Dag 1 – Data verzamelen en voorbereiden Introductie tot Microsoft Fabric De relatie tussen Fabric en Power BI Werken met workspaces en Fabric-items OneLake, Lakehouse en Data Warehouse Data laden met Dataflows Gen2 Data verwerken met Data Pipelines Werken met Bronze-, Silver- en Gold-lagen Monitoring van dataflows en pipelines Dag 2 – Modellen, rapporten en beheer Dimensioneel modelleren in Fabric Een stermodel bouwen Semantic models maken Direct Lake, Import en DirectQuery vergelijken DAX-measures en relaties toevoegen Row-level security instellen Power BI-rapporten bouwen Werken met deployment pipelines Monitoring Hub en Capacity Metrics App Performanceproblemen analyseren Praktijk Tijdens de training bouw je een complete analytics-oplossing voor een fictieve retailorganisatie. Je gaat onder andere: brondata inladen; data opschonen en transformeren; een Lakehouse inrichten; een Data Pipeline maken; een stermodel opbouwen; een Direct Lake semantic model maken; een Power BI-rapport ontwikkelen; beveiliging instellen; de oplossing uitrollen; capaciteit en prestaties monitoren. Voorkennis Voor deze training heb je ervaring nodig met: Power BI Desktop; Power Query; datamodellering; DAX; publiceren naar de Power BI-service. Ervaring met SQL is handig, maar niet verplicht. Ervaring met Spark, notebooks of Lakehouses is niet nodig. Trainingsvorm De training bestaat uit korte uitleg, demonstraties en veel praktische oefeningen. Je werkt gedurende beide dagen aan één doorlopende case. Duur 2 dagen Niveau Gemiddeld Resultaat Na afloop kun je zelfstandig een eenvoudige end-to-end Microsoft Fabric-oplossing ontwerpen, bouwen, beveiligen, publiceren en monitoren. Je begrijpt bovendien hoe je bestaande Power BI-oplossingen kunt doorontwikkelen naar een schaalbare Fabric-architectuur. Inclusief Digitaal cursusmateriaal Stapsgewijze labs Voorbeelddata Power Query-, SQL- en DAX-voorbeelden Architectuurvoorbeelden Checklist voor deployment Checklist voor monitoring en troubleshooting Samenvatting Maak de stap van Power BI developer naar Microsoft Fabric analytics developer. Bouw in twee dagen een complete oplossing met OneLake, Dataflows Gen2, Data Pipelines, een semantic model, Direct Lake en Power BI.

OVERVIEW The Dell PowerEdge Server Concepts training introduces PowerEdge server product concepts and related technologies. The course consists of four modules that focus on the fundamental concepts of the current Dell PowerEdge server technologies. The fundamental concepts include an introduction to servers, server networking, server maintenance, and server security and data protection. The training provides learners with the technical characteristics, attributes, and elements that define the PowerEdge portfolio. The course focuses on the technologies used in the 15th, 16th, and 17th generation of PowerEdge servers. Updated 28/07/2026   OBJECTIVES Upon successful completion of this training, participants should be able to: Describe the PowerEdge server portfolio, server storage components, and the supported RAID technologies Discuss the elements of the physical and network layers of the OSI model that include the different types of Ethernet cables, Ethernet speeds, and Ethernet standards. Follow common service practices, cautions, and component replacements. Analyze server security and data backup solutions. CONTENT The content of this training is designed to support the training objectives.  Module 1: Server Introduction and Storage Concepts Servers 1- Dell PowerEdge Servers a- Server form factors (Tower, Rack, Modular, XE, XR) b- Model nomenclature 2- Technology Evolution - CPU, memory, PCIe, and network advancements across generations 3- Server Overview - Server characteristics and client server architecture 4- Server Network Storage a- DAS, NAS, SAN, Cloud storage b- Storage capacity planning 5- Components of Storage - SATA, SAS, SSD, NVMe, E3, BOSS, NVDIMM, Backplane, Intel Optane RAID Concepts 1- Introduction to RAID - RAID levels (0, 1, 3, 5, 6, 10, 50, 60) 2- RAID Implementation - Matching RAID levels to use cases 3- Virtual Memory - Concepts and benefits Server Management Tools 1- Common Management Tools - iDRAC, Lifecycle Controller, RACADM, OpenManage 2- Server Setup and Configuration Utilities - System Setup, Boot Manager, Lifecycle Controller 3- Lifecycle Controller - Features and use cases 4- PowerEdge Management with the iDRAC UI - Licensing tiers and capabilities 5- Supported Operating Systems and Compatibility - VMware, Windows, Red Hat, Ubuntu, SUSERack Integration Module 2: Networking Fundamentals Networking Introduction 1- Network nodes and architecture 2- OSI model layers Physical and Network Layers 1- Ethernet Overview - Ethernet standards, identifiers, and broadcast domains 2- Physical Layer: Cabling and Connectors a- Twisted-pair cables (UTP vs STP) b- SFP, QSFP, and patch cables 3- Physical Layer: On-Board Network Cards a- LAN on Motherboard (LOM) b- Open Compute Project (OCP) NICs 4- Network Layer: Internet Protocol a- IPv4 and IPv6 b- IP classes, subnetting, and addressing c- Static vs dynamic IPs Application Layer 1- Session and Application Layer Overview - Server roles and application communication 2- Application Layer: Common Applications a- DHCP, ARP, DNS, NTP b- Email and file transfer protocols (SMTP, POP, IMAP, FTP, SFTP, TFTP, HTTP) Virtualization 1- Virtualization Overview - Benefits and infrastructure 2- Hypervisors and Virtual Machines a- Bare metal vs hosted hypervisors b- Hyper-V and VMware ESXi requirements 3- Virtual Networks - Private, internal, and external switches Server-Based Solutions 1- File Sharing Solution - Server selection, OS, network configuration, and security 2- High-Performance Computing (HPC) Solution - Compute nodes, storage, networking, and cluster management 3- Generative AI Solution - AI-optimized servers, storage, and software stack Module 3: Server Maintenance Introduction 1- Introduction to Server Maintenance 2- ElectroStatic Discharge (ESD) 3- Hardware Servicing Practices Server Components 1- 3D Simulators 2- Common Server Components 3- System Board Architectures 4- Easy Restore 5- CPUs, GPUs, DPUs 6- Server Memory 7- PowerEdge RAID Controller (PERC) 8- Backplanes 9- Onboard Cards 10- Risers and Expansion Cards Power and Cooling 1- Power Supply Unit (PSU) 2- Server Cooling 3- Fans and Air Shrouds Maintenance and Monitoring 1- Resources and Downloads 2- Configuration and Change Management 3- Configuration Profiles 4- Hardware Status Monitoring 5- iDRAC Maintenance Menu 6- Logs 7- iDRAC Troubleshooting Features 8- Common Windows and Linux Monitoring 9- Performing a Shutdown Module 4: Security and Data Protection Server Security 1- Server Security Overview a- Physical and digital security b- Site security practices 2- Server Security Features a- Boot Guard b- TPM 2.0 c- Secure Boot d- Lockdown Mode e- CPU Security 3- BIOS, UEFI, and CMOS - Boot modes and system configuration 4- Trusted Platform Module (TPM) - Authentication, attestation, and Secure Component Verification (SCV) 5- Authentication and Authorization - Role-based access, ACLs, and protocols (LDAP, FIDO, etc.) 6- iDRAC UI Restrictions and Security - User roles, lockdown mode, and access control 7- Secure Connect Gateway - Monitoring, diagnostics, and automated support Data Protection and Backup 1- Introduction to Backup - Backup topology and server roles 2- Backup Storage Solutions a- Primary, backup, and archival storage b- Dell PowerStore, PowerScale, PowerVault, LTO, PowerProtect 3- Running Backups and Frequency a- Backup scheduling, retention, and integrity b- Dell Cloud Clinical Archive (DCCA) 4- Restoring and Validating Data - Recovery planning and testing

Deze training is specifiek ontworpen om medewerkers de nodige kennis en vaardigheden bij te brengen om veilig en effectief om te gaan met de opslag van gevaarlijke stoffen volgens de richtlijnen van P PGS 15 is een richtlijn in Nederland die regels en eisen stelt aan de opslag van gevaarlijke stoffen. Het doel van deze richtlijn is om de veiligheid te waarborgen en risico's voor mens en milieu te minimaliseren. Wanneer je meer dan 2.500 kg aan gevaarlijke stoffen opslaat, is het volgens PGS 15 verplicht om minimaal één deskundige in dienst te hebben die kennis heeft van de juiste omgang met en opslag van deze stoffen. Dit helpt ervoor te zorgen dat alle veiligheidsprocedures correct worden gevolgd en dat eventuele incidenten snel en effectief kunnen worden aangepakt. Het doel van de training PGS 15 is om deelnemers inzicht te geven in essentiële veiligheidsaspecten bij de opslag van gevaarlijke stoffen. De training richt zich op: Omgevingsveiligheid: Minimaliseren van risico's voor milieu en omgeving. Arbeidsveiligheid: Waarborgen van veiligheid en gezondheid van werknemers. Brand- en rampenbestrijding: Voorbereiden op effectieve reacties bij noodsituaties. Deze aspecten helpen medewerkers om te voldoen aan PGS 15 en een veilige opslagomgeving te creëren.

OVERVIEW This course is an immersive, hands-on training course designed to equip IT professionals, solution architects, and business technologists with the skills to design, build, and manage intelligent AI agents using Microsoft Copilot Studio. Participants will gain practical experience creating both conversational and autonomous agents that integrate seamlessly with Microsoft 365, Power Platform, and enterprise data sources. Through guided labs, real-world examples, and advanced customization exercises, learners will develop the confidence to deploy secure, scalable Copilot agents that enhance productivity, automate workflows, and transform organizational processes. This course blends conceptual understanding with hands-on application, progressing from foundational Copilot principles to advanced orchestration, governance, and autonomous agent design.   Updated July 2026 OBJECTIVES After this course participants should be able to: Create and configure copilots using Microsoft Copilot Studio. Design conversational experiences using topics, entities, and generative AI capabilities. Integrate copilots with Microsoft 365, Power Platform, and external data sources. Implement actions and workflows to automate business processes. Configure authentication, security, and user access settings for copilots. Test, publish, and manage copilots for organizational use. Monitor copilot performance and optimize responses to improve user experience. AUDIENCE This course is designed for professionals who want to build or manage intelligent agents using Microsoft Copilot Studio, including: - Power Platform Makers and Developers who wish to extend their automation capabilities with AI-driven agents. - IT Administrators and Solution Architects responsible for deploying and governing AI solutions within Microsoft 365 environments. - Business Analysts and Citizen Developers looking to create task-specific copilots without extensive coding. - AI and Automation Specialists who want to design secure, autonomous, and scalable Copilot agents for enterprise use cases. CERTIFICATION None NEXT STEP None CONTENT Module 1 – Copilot Chat and Agents Introduce participants to Microsoft Copilot Chat and the concept of agents within the Microsoft 365 ecosystem. Learners will explore how Copilot serves as the AI interface for users and how agents extend its capabilities to perform tasks, retrieve data, and automate workflows. Understanding Microsoft Copilot Overview of Copilot in Microsoft 365 (Teams, Word, Outlook, and more) How Copilot Chat enhances productivity through conversational AI “Copilot lite” vs “Full Copilot” capabilities How Copilot integrates with organizational data and permissions Introducing Agents Definition and purpose of Copilot Agents Types of agents: Simple, Task-based, and Autonomous Example scenarios: IT Helpdesk Bot, HR Policy Assistant, Project Tracker How agents interact with Copilot Chat Deployment and Security Where agents run: Teams, web, and Power Platform environments Data governance, privacy, and compliance considerations Licensing, cost control, and telemetry tracking Lab 1: Build agents in Copilot Studio Lite Experience Module 2 – Building Agents with Copilot Studio This module provides a deep dive into the architecture, core capabilities, and authoring experience of Microsoft Copilot Studio. Participants will learn how Copilot Studio operates within the Microsoft ecosystem, understand its performance and governance considerations, and develop hands-on skills in building conversational agents using the authoring canvas and its core components followed by an introduction to its advanced tools, orchestration features, and generative AI integration. Through guided instruction and a practical lab, learners will design, author, and deploy a fully functional conversational agent using variables, entities, and structured conversation flows. Copilot Architecture and Core Capabilities Overview of Copilot Architecture and its role in the Microsoft 365 and Power Platform ecosystem Copilot Studio Core Capabilities – building, deploying, and managing conversational and autonomous agents Copilots and Conversational AI – the evolution from chat-based interaction to orchestrated reasoning Understanding conversation volumes, quotas, and limits for performance management Performance optimization and telemetry insights for efficient operations Planning and Lifecycle Management Planning your agent – defining purpose, scope, target users, and measurable outcomes The Typical Copilot Studio Lifecycle: Initiate → Prepare → Design → Build → Deploy → Operate → Optimize Selecting the right tools for your governance requirements Citizen, Partnered, and Pro Developer governance zones Role-based permissions and security boundaries Leveraging the Power Platform Center of Excellence (CoE) for governance, auditing, and analytics Copilot Studio Authoring Canvas Navigating the authoring canvas and understanding topic-driven design Using the Message Node to deliver static, dynamic, or formatted responses Using the Question Node to capture user input and enable conditional branching Creating rich text responses (hyperlinks, adaptive cards, lists, media) Using variables to navigate customers to tailored content Defining entities and slot-filling for structured data collection Topic management – organizing and linking topics for efficient conversation flow Using enhanced speech authoring capabilities for voice interactions Productivity and pro-code options – integrating Power Fx, expressions, and custom logic Lab 2: Build a conversational agent in Copilot Studio Agent Tools, Knowledge, and Orchestration Overview of Agent Tools within Copilot Studio Connecting Knowledge Sources for grounding answers and context Using Tools to extend agent capabilities: Copilot Connectors – integrate with Microsoft 365, Dynamics 365, and external APIs Computer Use Tool – automate interactions with desktop or web apps Code Interpreter – execute Python code directly within Copilot Studio Advanced Approvals – automate multi-level approval processes Leveraging the Orchestrator to coordinate multi-topic, multi-tool execution Designing Prompts effectively for contextual, human-like responses Generative AI and Optimization Generative AI in Copilot Studio – enabling AI reasoning and dynamic responses Generative building – AI-assisted topic creation and optimization Generative answers – grounded, data-informed AI responses How Retrieval-Augmented Generation (RAG) supports accuracy and reliability Using analytics to easily optimize with data-driven insights Tracking agent performance Measuring engagement and response accuracy Iterating designs based on telemetry Integration, Agent Flows, and Multi-Agent Orchestration Designing Agent Flows for end-to-end automation Multi-agent orchestration – coordinating several specialized agents to handle complex workflows Planning integrations with Power Automate, Azure services, and external APIs Deploying and using agents in any system – Teams, web, Dynamics 365, or embedded applications Lab 3: Use tools in Copilot Studio Module 3 – Building Autonomous Agents This module introduces the concept of autonomous agents within Microsoft Copilot Studio and explores how they extend beyond conversational interactions to perform independent, goal-oriented actions. Learners will understand the difference between conversational and autonomous agents, explore the core components that enable autonomy, and learn how to craft precise, ethical, and effective agent instructions. Through guided demonstrations and practical exercises, participants will design the foundational structure of an autonomous agent, integrating triggers, tools, and logic to automate business processes intelligently and responsibly. Understanding Autonomous Agents What Are Autonomous Agents? Definition and evolution of autonomous agents within Microsoft Copilot Studio How autonomous behavior enhances business automation and decision-making Examples of autonomous agents in real-world enterprise scenarios (approvals, notifications, data insights) Conversational vs Autonomous Agents Key differences in purpose, behavior, and user interaction Conversational agents: reactive and guided by prompts Autonomous agents: proactive, event-driven, and task-focused Choosing the right agent type for your business process Reinventing Business Processes with Agents How autonomous agents can reimagine workflows across departments Mapping manual processes to autonomous agent capabilities Best practices for balancing automation with control and accountability Crafting Autonomous Agent Instructions The Art of Instruction Design Writing clear, structured agent instructions Defining role, tone, scope, and context for autonomous behaviour Handling ambiguity, uncertainty, and ethical constraints Building Blocks of Writing Agent Instructions Purpose statement Behavioural rules and escalation paths Contextual memory and grounding Error handling and safety checks Examples of well-structured vs poorly written instructions Building Blocks of an Autonomous Agent Core Components of Autonomy Triggers: initiating events that activate agents (manual, scheduled, event-driven) Tools: actions and connectors that allow agents to perform work Knowledge: content sources and grounding data Instructions: defining how agents reason and respond Designing multi-step workflows with Copilot Studio tools and triggers Understanding dependencies, data flow, and governance boundaries Lab 4: Make your agent autonomous in Copilot Studio Module 4 – Language & Orchestration This module focuses on how Microsoft Copilot Studio interprets, processes, and orchestrates natural language to deliver accurate, contextual, and human-like responses. Learners will explore language understanding models, orchestration types, and best practices for building intelligent agents that can manage ambiguity, route topics effectively, and deliver consistent communication across languages and scenarios. Natural Language Understanding (NLU) in Copilot Studio Overview of Natural Language Understanding and its role in conversational AI How Copilot interprets intent, entities, and context from user input Comparison of language processing models: Classic Orchestration (topic-based routing) Generative Orchestration (AI-driven reasoning and chaining) The evolution from rule-based intent matching to generative orchestration Orchestration Models and Logic Classic Orchestration How Copilot matches user intent to predefined topics Topic routing, priority, and fallback mechanisms Using disambiguation prompts when multiple intents are detected Disambiguation and Orchestration Strategies for managing ambiguous queries Designing topic structures for clear and efficient disambiguation Example: differentiating between “request access” vs. “reset password” topics Generative Orchestration How Copilot uses generative AI to route across tools, topics, and data The orchestration engine: connecting tools, knowledge sources, and actions Combining structured (classic) and generative (adaptive) orchestration for hybrid agents How orchestration improves responsiveness, reduces errors, and automates complex reasoning How Tools and Topics Are Orchestrated Role of the orchestrator in managing flow between topics and tools Understanding priority, context retention, and handoffs Integrating multiple data sources or services within a single agent session Designing for Clarity and Effectiveness Best Practices for Agent Instructions Writing clear, concise, and contextual instructions for accurate orchestration Controlling tone, scope, and fallback responses Using grounding and constraints to ensure reliable generative outputs Best Practices for Topic Inputs & Outputs Defining input and output expectations for each topic Using metadata and variable binding for consistent data transfer Creating well-structured topic hierarchies to reduce confusion and error loops Language Control and Localization What Controls the Agent Language Role of AI models, user preferences, and system settings in language handling Managing multilingual environments with consistent tone and structure Auto-Detect Spoken Language How Copilot Studio detects and adapts to user language automatically Best practices for supporting multilingual users (voice and text) Configuring fallback or default language options for enterprise scenarios Module 5 – AI capabilities This module introduces learners to the power of Retrieval-Augmented Generation (RAG) and how it enhances Copilot Studio agents with accurate, grounded, and secure generative responses. Participants will explore how RAG architecture operates within Copilot Studio, how to connect and manage knowledge sources effectively, and how to safely infuse generative AI capabilities into topic designs while maintaining compliance and reliability. How RAG Enhances AI Responses Understanding Retrieval-Augmented Generation (RAG) and why it’s essential for enterprise-grade AI The limitations of pure generative AI (hallucination, context drift, factual inaccuracy) How RAG combines retrieved data from trusted knowledge sources with generative reasoning Benefits of RAG in Copilot Studio: Grounded responses based on organizational data Context retention and relevance in extended conversations Reduced risk of misinformation or unsupported answers Real-world examples: HR policy retrieval, compliance support, and project insights RAG Architecture in Copilot Studio Overview of RAG architecture within the Microsoft Copilot ecosystem The retrieval layer: indexing, search, and grounding data pipelines The generation layer: contextual synthesis using large language models (LLMs) How Copilot Studio manages context windows, relevance scoring, and ranking Integrating with Microsoft Graph, SharePoint, Dataverse, and external data repositories Understanding caching, latency, and query optimization in RAG-based designs Knowledge Sources and Generative AI Defining knowledge sources in Copilot Studio SharePoint document libraries Dataverse tables External data via connectors or APIs How Copilot Studio uses knowledge sources to ground generative responses Techniques for data curation and preparation for RAG indexing Integrating structured and unstructured data into your Copilot agent How Generative AI interacts with these sources to produce reliable, factual answers Generative AI Security and Compliance Considerations Data protection in generative AI workflows How Copilot Studio handles sensitive or restricted content Managing compliance requirements (GDPR, data residency, retention policies) Understanding Responsible AI principles within Microsoft’s Copilot framework Limiting generative scope through instructions, topic constraints, and data access rules Setting boundaries for autonomous or open-ended responses Infusing Generative AI into Topics Methods for embedding generative capabilities directly within topics Enabling Generative Building and Generative Answers in Copilot Studio Designing hybrid topics that use both structured and generative logic Writing grounded prompts that combine user input, retrieved knowledge, and AI synthesis Testing and refining generative topics to ensure consistency, tone, and accuracy Module 6 – Integrations This module explores how to integrate Copilot Studio agents with enterprise systems and external data sources using connectors, flows, APIs, and automation tools. Learners will understand key integration patterns, performance constraints, and quotas, as well as how to extend Copilot capabilities through custom connectors, HTTP requests, and the Model Context Protocol (MCP). Integration Patterns and Considerations Overview of integration architecture within Copilot Studio and the Power Platform Integration patterns: Direct integration (connectors and HTTP actions) Event-driven orchestration (Power Automate flows) Data-driven integration (Dataverse, APIs, Azure Logic Apps) Choosing the right integration model based on scalability, latency, and control Security considerations for data flow and authentication (OAuth, managed identity, service principal) Quotas, Limits, and Performance Understanding Copilot Studio integration quotas and limits (calls per minute, session size, data throughput) Performance tuning strategies for efficient agent workflows Managing API throttling, retries, and error handling in long-running tasks Using telemetry and analytics to monitor connector and flow performance How to design integrations that minimize cost and resource consumption Agent Flows, HTTP Actions, and Connectors Introduction to Agent Flows in Copilot Studio for orchestrating integrations Using HTTP actions for RESTful API calls and external service integration Working with standard connectors (SharePoint, Outlook, Teams, Azure, Dynamics 365, Dataverse, etc.) Designing connector-based actions to extend agent functionality Handling timeouts and long-running processes in cloud flows Best practices for async processing and status callbacks Managing cloud flow timeouts gracefully with user feedback loops Custom Connectors and Advanced Integration Overview of Custom Connectors in Copilot Studio and Power Platform How to build and register a custom connector for internal or external APIs Using Swagger/OpenAPI definitions to define connector actions and responses Testing and validating custom connectors in sandbox environments Governance considerations for connector publishing and sharing Integration with Azure Functions and Logic Apps for extensibility Model Context Protocol (MCP) Introduction to the Model Context Protocol (MCP) and its role in AI-driven integrations How MCP enables Copilot agents to securely access external data models Using MCP to extend Copilot with contextual understanding from multiple systems Best practices for maintaining data integrity and compliance in MCP-connected agents Computer-Using Agents (CUA) and RPA Understanding Computer-Using Agents (CUA) – what they are and how they work Enabling agents to interact with desktop applications and web browsers Comparing CUA and Robotic Process Automation (RPA): RPA for structured, rule-based workflows CUA for intelligent, adaptive automation through AI orchestration Building integrated processes that combine cloud flows, connectors, and CUAs Example use cases: Reading data from legacy apps Filling forms or automating reports Coordinating actions between on-premises and cloud systems Module 7 – Security, monitoring & governance This module equips learners with the knowledge and best practices needed to secure, monitor, and govern Microsoft Copilot Studio environments at scale. Participants will learn how to balance innovation and control, implement zoned governance models, enforce data loss prevention (DLP) and compliance policies, and manage the security of both agents and users. Balancing Innovation and Governance The importance of governance in AI and Copilot deployment Balancing citizen development and enterprise oversight How governance enables safe innovation without stifling productivity Building governance frameworks aligned with corporate IT and security policies Common governance challenges in scaling Copilot adoption The Agent Controls Model Understanding the Agent Controls Model: policies, permissions, and oversight Key governance layers: user, environment, tenant, and data How agent-level controls support compliance and operational transparency Tracking agent performance and telemetry for security auditing Zoned Security, Governance, and Operations Overview of Governance Zones (1–3): Zone 1: Citizen Development (low-risk, innovation sandbox) Zone 2: Partnered Development (moderate risk, departmental use) Zone 3: Pro Development (high governance, enterprise-critical) Mapping organizational maturity to governance zones Getting Started with Zones – setting up secure, scalable environments How to manage transitions between zones while maintaining compliance Security and Administration Controls Overview of security architecture in Copilot Studio and Power Platform Security, agent, and user management strategies: Assigning roles and permissions Enabling secure authentication (Azure AD, Entra ID) Monitoring user actions and agent activity logs Designing an effective environment strategy for production, test, and development Understanding Copilot Studio security roles and least-privilege access design Data Loss Prevention (DLP) and Policy Management Overview of DLP Policies in Power Platform and Copilot Studio The role of DLP connectors and data classification in controlling data flow How to manage connectors across risk profiles (Business vs. Non-Business) DLP policies and rules per environment — and when they can be safely relaxed Designing DLP frameworks that balance flexibility and compliance Practical examples: blocking external connectors, auditing data access Securing Copilot Studio Usage at Scale Strategies for secure scaling across large organizations Controlling adoption through environment boundaries and sharing rules Using analytics and reports to monitor agent performance, cost, and usage Automating governance checks and policy enforcement through CoE Starter Kit Prompt Injection Mitigations – preventing manipulation of agent behavior through malicious inputs DDoS Protection for Anonymous Chatbots – safeguarding public-facing Copilots against overload attacks Data Residency and Compliance Management Understanding data residency and storage in Microsoft Copilot Studio Managing data movement restrictions across geographies and tenants Compliance with GDPR, SOX, HIPAA, and other global standards Designing for multi-region governance and local data processing Tools and best practices for monitoring data movement and access patterns Module 8 – Application Lifecycle Management This module focuses on implementing Application Lifecycle Management (ALM) practices for Copilot Studio. Learners will explore how ALM ensures structured development, testing, and deployment of Copilot agents across environments while maintaining governance, consistency, and control. Participants will gain practical insights into using Power Platform ALM, Azure DevOps, GitHub Actions, and Power Platform Pipelines to manage agent updates and continuous delivery in enterprise environments. Understanding ALM Strategy Defining an ALM strategy for Copilot agents within Microsoft 365 and Power Platform Why ALM is essential for enterprise-scale development and governance The benefits of structured lifecycle management: Version control Testing and quality assurance Controlled deployment across environments Reduced risk and rework Aligning ALM practices with organizational change management and security policies What Is ALM and Why It’s Important Overview of Application Lifecycle Management (ALM) concepts Development → Testing → Staging → Production cycles Managing agent versions and configurations How ALM supports collaboration between makers, developers, and administrators Common pitfalls in unmanaged agent updates or direct publishing Real-world ALM examples in Copilot Studio agent deployment What “Publish” Really Does in Copilot Studio Understanding the Publish process in Copilot Studio What happens behind the scenes when publishing an agent Version creation, environment packaging, and synchronization How publishing differs from exporting/importing solutions in Power Platform Best practices for publishing safely without disrupting production agents Integrating publishing into your broader ALM workflow Power Platform ALM for Copilot Studio Overview of Power Platform ALM capabilities relevant to Copilot Studio How solutions encapsulate Copilot agents, connections, and data configurations Managing Copilot components as part of broader Power Platform solutions Understanding environments and their role in ALM: Development, Test, UAT, and Production Environment permissions, data boundaries, and DLP alignment Tracking agent versions, dependencies, and solution history ALM with Azure DevOps Integrating Azure DevOps with Power Platform and Copilot Studio Managing Copilot solution source control and version tracking Automating deployment pipelines through Azure DevOps YAML templates Example workflows: Export → Validate → Deploy Trigger-based deployments for agents or connectors Using Azure DevOps Boards for ALM governance and change tracking GitHub Actions for Microsoft Power Platform Introduction to GitHub Actions for CI/CD with Power Platform Setting up a GitHub repository to manage Copilot Studio solutions Example automation: Exporting a solution from Dev → Importing to Test or Prod Running validation checks before deployment Comparing Azure DevOps Pipelines vs. GitHub Actions for ALM workflows Security and permission considerations for GitHub integrations Power Platform Pipelines for Copilot Studio Introduction to Power Platform Pipelines — no-code ALM for citizen and pro developers How Pipelines simplify solution promotion across environments Configuring automated pipelines for Copilot Studio agents Using deployment profiles to control environment variables and data connections Monitoring deployment success, rollback procedures, and version tracking Combining Pipelines, GitHub, and DevOps for hybrid ALM strategies Module 9 – Analytics & KPIs This module teaches learners how to measure, analyze, and optimize the performance of Copilot Studio agents using data-driven insights. Participants will explore conversation analytics, engagement metrics, and key performance indicators (KPIs) that reflect business impact and user satisfaction. By implementing a structured analytics and optimization strategy, learners will be able to continuously improve their agents’ effectiveness, refine conversation design, and demonstrate ROI to stakeholders. Conversation Design and Outcome Tracking Understanding conversation analytics in Copilot Studio Measuring conversation flow effectiveness: intent recognition, success paths, and drop-off points Designing conversations with measurable outcomes (e.g., task completion, satisfaction, resolution rates) Tracking end-user interactions and intent success using telemetry and built-in analytics Mapping conversational outcomes to business objectives and performance goals Using conversation data to refine prompts, topics, and agent logic Engagement and Outcomes Defining and measuring engagement metrics: Total users, active sessions, conversation depth, and dwell time Repeat interactions and user satisfaction trends Identifying key engagement drivers — tone, context, personalization, and response time Using data to segment audiences and identify high-value user scenarios Correlating agent engagement with organizational productivity and ROI Example KPIs: Resolution rate per topic Time-to-response improvement Reduction in support tickets through automation Business cost savings from AI adoption Analytics Strategy Building a comprehensive analytics strategy for Copilot agents Aligning analytics goals with business priorities and governance policies Defining measurable KPIs for agent performance and value realization Using Microsoft analytics tools: Copilot Studio Analytics Dashboard Power BI integration for advanced reporting Dataverse telemetry for raw data analysis How to combine Copilot analytics with Power Platform CoE dashboards Tracking metrics across environments: Dev, Test, and Production Data governance considerations in analytics — ensuring accuracy and privacy Optimization Strategy Developing an optimization cycle for continuous improvement: Monitor → 2. Analyze → 3. Adjust → 4. Deploy → 5. Measure again Leveraging A/B testing for topic or prompt improvements Applying analytics insights to refine: Agent tone and conversational flow Topic hierarchy and orchestration logic Knowledge source selection and generative AI prompts Using performance data to identify underperforming agents or topics Creating a feedback loop with stakeholders and users for ongoing tuning Setting thresholds and alerts for critical KPIs (e.g., low satisfaction, high failure rate Module 10 – Licensing and capacity This module provides learners with a deep understanding of how Microsoft Copilot Studio licensing and capacity consumption work within the Power Platform ecosystem. Participants will learn how to plan, monitor, and manage Copilot Studio resource usage across environments while maintaining cost efficiency and operational scalability. Licensing and Capacity Overview Overview of Copilot Studio licensing models Licensing through Microsoft 365, Power Platform, and standalone Copilot subscriptions Key licensing dependencies: Power Virtual Agents, Power Automate, Dataverse Capacity components and what they represent: Dataverse storage (database, file, log) Power Platform request limits AI Builder and Copilot Studio usage entitlements Aligning licensing strategy with your organization’s scale, user base, and governance zones How to assign and manage licenses across tenants and environments Basic Credit Consumption Scenarios Understanding Copilot capacity credits and how they are consumed Common usage patterns that drive credit consumption: Agent interactions and conversation sessions Generative AI responses and knowledge retrieval Tool usage (code interpreter, connectors, RAG queries) Mapping agent types to credit requirements (simple, task-based, autonomous) Real-world credit usage examples for typical Copilot deployments How conversation complexity, orchestration, and integration affect credit burn Agent Activity and Billing Rates Understanding Agent Activity metrics and their impact on billing How billing rates differ based on: Generative AI vs. retrieval-based responses Tool and connector usage Frequency of orchestration or autonomous agent actions Reading and interpreting usage reports in the Power Platform admin center Using telemetry data to connect activity metrics to cost drivers Best practices for minimizing unnecessary agent calls and redundant executions Understanding Credit Burn Rate Definition of credit burn rate in Copilot Studio How to monitor and project credit consumption across environments Factors influencing burn rate: Agent concurrency and scaling Number of active users or sessions Size and complexity of AI prompts and retrieval operations Strategies for managing and reducing burn rate: Optimizing conversation length and efficiency Reusing knowledge sources and cached responses Scheduling non-critical agents during off-peak hours Setting up alerts or dashboards to track consumption trends Copilot Studio Estimator Introduction to the Copilot Studio Estimator Tool How to use the estimator to forecast usage, licensing, and costs Simulating scenarios based on: Number of agents Daily conversation volume Generative AI usage patterns Interpreting estimator outputs to guide budget and capacity planning Integrating estimator results into business case and ROI modeling Capacity Management Building a capacity management strategy for Copilot Studio Monitoring capacity in the Power Platform Admin Center Allocating capacity per environment and adjusting for usage growth Using governance zones and environment strategy to balance capacity Managing cross-tenant capacity sharing and reporting Planning for scale: forecasting enterprise-wide usage Coordinating with IT operations and finance teams for ongoing monitoring Module 11 – Testing agents This module teaches learners how to effectively test, validate, and ensure quality for Copilot Studio agents before deployment. Participants will explore Copilot Studio Kit testing capabilities, learn how to test agents at scale, and understand the types of tests supported within the Copilot Studio ecosystem. By applying structured testing practices, learners will develop the skills to identify defects, improve performance, and deliver reliable, production-ready Copilot agents that align with enterprise standards. Introduction to Testing in Copilot Studio The importance of testing and validation in the Copilot agent lifecycle How testing fits into the Application Lifecycle Management (ALM) and deployment process Typical challenges in testing AI-driven and conversational systems Core goals of agent testing: Ensuring accuracy, reliability, and usability Verifying data access and security Confirming proper orchestration and workflow logic Overview of the Copilot Studio Kit Introduction to the Copilot Studio Kit and its testing capabilities Components of the Kit: Test automation framework Reporting and analytics tools Configuration and environment setup utilities How the Kit integrates with Power Platform, Azure DevOps, or GitHub Actions pipelines Preparing the testing environment and data sets Using the Kit for continuous testing in multi-environment deployments Testing Agents at Scale Strategies for scaling agent testing across multiple environments and use cases Simulating large-scale user interactions and load testing scenarios Managing and tracking test execution across Dev, UAT, and Production environments Automating tests as part of CI/CD pipelines (DevOps or GitHub Actions) Monitoring performance and response times under real-world usage conditions Identifying and resolving issues related to: Latency and orchestration delays Data retrieval and grounding (RAG) errors Tool integration failures or misconfigurations Ensuring governance compliance during automated test runs Supported Test Types in the Copilot Studio Kit Overview of test types supported in Copilot Studio Kit: Unit Tests: Validate individual topics, nodes, and responses Integration Tests: Verify that connectors, triggers, and tools function correctly together Regression Tests: Ensure existing functionality remains stable after changes or updates Performance Tests: Evaluate speed, concurrency, and response times Security Tests: Validate DLP adherence, authentication, and permissions Conversational Flow Tests: Assess natural language understanding, disambiguation, and orchestration accuracy Best practices for selecting appropriate test types for each phase of development How to interpret test results and generate actionable reports Additional Labs: The following labs have been provided in order to gain additional hands on learning experience with Copilot Studio. They augment the labs aligned to each module and should be carried out once all the previous labs have been completed if the course is run other 3 days: Advanced Lab 1: Create a Monthly Business Review (MBR) Agent Advanced Lab 2: Build an Autonomous Account News Assistant Agent Advanced Lab 3: Track conversation outcomes and user feedback on AI responses Advanced Lab 4: Autonomous Portfolio Lookup Agent with Computer-Using Agents (CUA) Advanced Lab 5: Deliver high-quality, scalable agents with Copilot Studio Kit Advanced Lab 6: Model Context Protocol (MCP) & Copilot Studio

OVERVIEW Get the knowledge and skills to build, manage, and secure a VMware Cloud Foundation (VCF) Private Cloud version 9.1. This five-day course provides knowledge and skills on VCF architecture, licensing models, and Private Cloud components at both the fleet and instance levels. The course covers end-to-end fleet deployment using the VCF Installer, post-deployment tasks including VCF Operations component setup, and fleet management through Single Sign-On configuration, VCF Identity Broker, role-based access control, and credential management. Participants, through hands-on labs,  will also deploy and manage workload domains, configure VMware NSX networking with Virtual Private Cloud constructs and Transit Gateway configurations, and manage vSAN storage using policies, fault domains, and VCF Operations monitoring tools. The course also covers VCF certificate management using SDDC Manager with Microsoft CA, OpenSSL CA, and third-party certificate authorities. Participants will perform lifecycle management operations including patching and upgrading VCF management and fleet components, and executing backup and restore procedures across the VCF fleet. In the VCF Security section, participants will define security, compliance, and resilience in VCF, assess compliance posture using Security Posture Management, monitor security health through the Security Operations Dashboard, and review audit trail events. The course concludes with VCF upgrade paths to version 9.1, covering supported upgrade scenarios from vSphere 8.0 and VCF 5.2 environments. Updated July 2026 OBJECTIVES By the end of the course, participants should be able to: Describe VMware Cloud Foundation architecture and Private Cloud components at the fleet and instance levels Deploy and configure a VCF Private Cloud using the VCF Installer, including networking, storage, and post-deployment tasks Manage VCF Fleet operations including SSO, RBAC, identity federation, workload domains, NSX networking, and vSAN storage Manage VCF lifecycle using the software depot, patch and upgrade VCF components, and implement backup and restore procedures Apply VCF security using Security Posture Management, the Security Operations Dashboard, certificate management, and supported upgrade paths to VCF 9.1 AUDIENCE System Administrators, Solution Engineers, Consultants, Architects, and Support Personnel CERTIFICATION - Specific certification for VCF 9.1 is not yet available.  CONTENT Module 1: Course Introduction Describe VMware Cloud Foundation components, architecture, and supported private cloud use cases Explain the VMware Cloud Foundation licensing model and available license types Outline the course curriculum covering deployment, fleet management, networking, storage, lifecycle, and security Module 2: VCF Private Cloud: Overview and Architecture Define VMware Cloud Foundation key features, use cases, and integrated security capabilities across all layers Explain the advanced services and operational capabilities of VMware Cloud Foundation Describe the VCF Private Cloud architecture including fleet-level and instance-level components Identify the various roles and capabilities within a VCF Private Cloud environment Module 3: VCF Private Cloud Deployment Identify VCF fleet deployment considerations and planning requirements using the Planning and Preparation Workbook Outline the sequence for deploying VCF Private Cloud including core component configuration Describe the deployment configuration of VCF instance and fleet management components Deploy a new VCF fleet using the VCF Installer wizard or a deployment specification JSON file Module 4: VCF Post-Deployment Tasks Explain VCF Operations for Networks, VCF Operations for Logs, and VCF Identity Broker deployment models Describe deployment considerations for VCF Operations components including Real-Time Metrics Deploy and navigate VCF Operations components and perform post-deployment management tasks Module 5: VCF Fleet Management Describe the VCF licensing model including capacity pooling, primary and add-on licenses, and 9.1 licensing procedures Configure VCF Single Sign-On and VCF Identity Broker deployment models for all VCF instance components Identify supported directories and identity providers and configure SSO enablement across VCF components Manage role-based access control, users, user groups, and credentials in VMware Cloud Foundation Outline password management workflows and available API options for automating credential management tasks Module 6: VCF Workload Domain Explain VMware Cloud Foundation workload domains and apply vSphere, network, and storage design considerations Describe design prerequisites and create workload domains using VCF Operations Configure vCenter linked groups and manage host and cluster additions within workload domains Import an existing vCenter as a workload domain using VCF Operations including applicable import limitations Module 7: VCF Networking Identify the core components of the NSX architecture including management, control, and data planes Describe NSX overlay networking concepts including Geneve encapsulation, TEP configuration, and Traceflow Explain Virtual Private Cloud constructs and configure VPC and VPC subnets in VMware Cloud Foundation Configure network connectivity during VCF Fleet deployment including Distributed and Centralized Transit Gateways Module 8: VCF Storage Management Describe VMware Cloud Foundation storage models including principal and supplemental storage options Explain vSAN networking and hardware requirements and configure vSAN clusters with appropriate storage policies Configure vSAN fault domains and manage vSAN cluster operations in VMware Cloud Foundation Analyze vSAN performance and generate storage reports using VCF Operations monitoring tools Module 9: VCF Certificate Management Describe public key infrastructure concepts including certificate signing requests and CA options in SDDC Manager Manage certificates in VMware Cloud Foundation using the SDDC Manager certificate management workflow Integrate VCF Operations with Microsoft CA and OpenSSL CA for certificate issuance and installation Install and manage certificates issued by Microsoft CA, OpenSSL CA, or third-party CAs in VCF Operations Module 10: VCF Lifecycle Management Identify the role of the software depot and configure it in VCF Operations to manage VCF fleet lifecycle Manage software depot content, storage, and bundle assignments in VCF Operations Upgrade and patch VCF management and fleet management components using lifecycle management workflows Configure backup and restore procedures for the VCF fleet using SFTP, SDDC Manager, and fleet management nodes Execute backup and restore operations for fleet-level and VCF management components Module 11: VCF Security Define security, compliance, and resilience principles and describe integrated security features across all VCF layers Assess compliance and manage security posture using Security Posture Management in VMware Cloud Foundation Monitor security health through the Security Operations Dashboard and analyze events using the Audit Trail Orchestrate unified Protection and Recovery workflows using VCF advanced networking and security capabilities Module 12: VCF Upgrade Paths Identify supported upgrade paths to VCF 9.1 including key considerations, prerequisites, and compatibility assessments Explain the upgrade process from vSphere 8.0 to VCF 9.1 using the existing vSphere deployment path Outline upgrade stages from vSphere 8.0 with multiple Aria components to VMware Cloud Foundation 9.1 Describe prerequisites and upgrade sequence from VCF 5.2 with Aria components to VMware Cloud Foundation 9.1 Differentiate between the existing vSphere upgrade path and the vCenter import process for transitioning to VCF 9.1

Wil je als leidinggevende bewuster schakelen tussen mensen, resultaten en organisatiebelangen? In deze driedaagse training versterk je jouw leiderschap met inzichten uit de organisatiepsychologie. Je ontdekt hoe jouw gedrag doorwerkt in samenwerking, motivatie en verandering. Met praktische handvatten en begeleiding van trainers uit de praktijk maak je bewustere keuzes en geef je doelgerichter leiding in uiteenlopende werksituaties. Deze training wordt binnen Eduvision verzorgd door Skills Alchemist, ons label voor trainingen op het gebied van human skills en organisatieontwikkeling, met de dienstverlening die je van Eduvision gewend bent. Algemene omschrijving Leidinggeven vraagt om meer dan alleen het aansturen van een team. Je schakelt voortdurend tussen mensen, resultaten en organisatiebelangen, terwijl je keuzes maakt in situaties die vaak meerdere belangen raken. In deze driedaagse training ontwikkel je jouw leiderschap vanuit inzichten uit de organisatiepsychologie. Je leert hoe jouw gedrag invloed heeft op samenwerking, motivatie en verandering en hoe je jouw leiderschapsstijl bewust afstemt op wat een situatie vraagt. De training begint met het versterken van het inzicht in jezelf als leider en de invloed van jouw gedrag op anderen. Vervolgens ontdek je hoe je mensen verbindt, motiveert en richting geeft in uiteenlopende situaties. Vanuit die basis werk je aan het begeleiden van verandering en het versterken van samenwerking binnen teams en organisaties. Tijdens de training werk je met herkenbare voorbeelden en praktijkgerichte oefeningen die direct aansluiten op situaties waarmee leidinggevenden dagelijks te maken hebben. De trainer brengt ruime ervaring mee vanuit verschillende organisaties en vertaalt inzichten steeds naar concrete toepassingen. Deze training bieden we ook als bedrijfstraining voor jou en je team De inhoud stemmen we dan af op jullie werksituatie, concrete vraagstukken, context en leiderschapsstijl  zodat de training direct aansluit op wat er binnen jouw organisatie speelt. Zo ontstaat een gerichte en praktische training waar je de volgende dag direct mee aan de slag kunt. Programma Tijdens de training Leiderschap voor Teammanagement komen in basis onderstaande onderwerpen aan bod. Afhankelijk van ontwikkelingen op het vakgebied, kan de feitelijke trainingsinhoud hier echter van afwijken. Bel ons gerust voor meer informatie over de actuele inhoud. Jouw leiderschap als vertrekpunt Inzicht in jouw leiderschapsstijl en de invloed daarvan op anderen Herkennen van overtuigingen, drijfveren en gedragspatronen Ontwikkelen van een leiderschapsstijl die past bij jouw rol en ambities Schakelen tussen mensen, resultaten en organisatiebelangen Bewust afwegen van verschillende belangen en verantwoordelijkheden Leidinggeven vanuit intrinsieke motivatie en eigenaarschap Omgaan met weerstand en uiteenlopende perspectieven Mensen in beweging brengen Voeren van gesprekken die verbinden, richting geven en uitdagen Herkennen van groepsdynamiek en gedrag binnen teams Creëren van vertrouwen, betrokkenheid en gezamenlijke verantwoordelijkheid Leidinggeven aan verandering Begrijpen hoe mensen reageren op verandering en onzekerheid Situationeel leidinggeven en bewust schakelen in leiderschapsstijl Bouwen aan weerbaarheid, ontwikkeling en duurzame samenwerking De training is interactief en praktijkgericht opgezet. Je werkt actief aan herkenbare situaties, met veel ruimte voor vragen en eigen voorbeelden. Door te oefenen en bespreken ervaar je hoe je jouw leiderschap bewust afstemt op verschillende situaties en met meer vertrouwen schakelt tussen mensen, resultaten en organisatiebelangen. De training wordt verzorgd door trainers uit de praktijk, die ervaring hebben in verschillende organisatiecontexten. We houden altijd rekening met jouw verwachtingen, zodat de training aansluit bij wat voor jou relevant is. Doelen Na deze training heb je handvatten om: Te schakelen tussen mensen, resultaten en organisatiebelangen Te herkennen hoe jouw gedrag invloed heeft op samenwerking, motivatie en prestaties Jouw leiderschapsstijl af te stemmen op verschillende situaties en behoeften Richting te geven aan verandering en omgaan met weerstand binnen teams Eigenaarschap en samenwerking te versterken binnen jouw team

Leer de fundamenten van de Go-taal, datastructuren, interfaces, generics en concurrency. In deze cursus bouw je een sterke basis in Go door te leren hoe Go-programma's zijn opgebouwd met packages en modules, hoe functies en methoden worden ontworpen en hoe interfaces polymorfisme mogelijk maken. Je oefent met onderdelen van de taal, zoals statements, strings en runes, slices, maps, error- en panic-afhandeling, en generics met type constraints. De cursus introduceert ook goroutines, channels en select voor concurrent programmeren, en laat het praktische gebruik zien van standaardbibliotheekpackages zoals bufio, cmp, crypto, sql, iter, log, math, net en os. - Explain Go program structure using packages, modules, imports, and initialization order [Understand] - Apply Go statements to write clear and correct control flow [Apply] - Apply Go core data types to represent and transform values safely [Apply] - Implement functions and methods using parameters, return values, receivers, and defer for predictable behavior [Apply] - Analyze interface-based designs, method sets, and type assertions for safe polymorphism [Analyze] - Implement generic workflows using type parameters and constraints [Apply] - Implement concurrent workflows using goroutines, channe…

Leer hoe u Microsoft 365, Copilot en AI-agenten kunt gebruiken om werkprocessen te automatiseren, de productiviteit te verhogen en de samenwerking te verbeteren. Deze cursus biedt een uitgebreide en diepgaande inleiding tot Microsoft 365, Copilot en AI-aangedreven agents. Deelnemers krijgen een grondig inzicht in de kernconcepten, belangrijkste diensten, beveiligingsfuncties en beheersmogelijkheden binnen het Microsoft 365-ecosysteem. Voortbouwend op deze basis wordt in de cursus onderzocht hoe Copilot en intelligente agents gebruikmaken van kunstmatige intelligentie om workflows te stroomlijnen, routinetaken te automatiseren, samenwerking te verbeteren en gepersonaliseerde gebruikerservaringen te bieden in alle Microsoft 365-toepassingen. Aan de hand van praktische inzichten en praktijkgerichte voorbeelden verwerven deelnemers de kennis die nodig is om AI-gestuurde productiviteitstools in moderne digitale werkomgevingen effectief in te voeren, te beheren en optimaal te benutten. * 12 maanden online toegang * Meer dan 7 uur e-learning * Measure-Up-examensimulatie – 110 vragen * Tips & trucs Deze cursus is ideaal voor: Beginnende IT-professionals die een basis willen leggen in Microsoft 365. Junior Microsoft 365-beheerders die beginnen met het beheren van Microsoft 365-omgevingen. Medewerkers van technische ondersteuning en helpdesks die met Microsoft 365 werken. Systeembeheerders met weinig of geen ervaring met Microsoft 365 Copilot. IT-medewerkers die willen leren hoe de door AI aangestuurde Copilot en agents de productiviteit verbeteren. Professionals die zich voorbereiden op een functie waarbij Microsoft 365-beheer en AI-gestuurde werkplekoplossingen een rol spelen. Iedereen die op zoek is naar een praktische inleiding tot Microsoft 365-services, Copilot en AI-agenten, zonder dat daarvoor eerdere praktijkervaring vereist is. Na het voltooien van deze cursus kun je: De architectuur van Microsoft 365 en de basisconcepten achter Microsoft 365 Copilot begrijpen. Identiteitsbeheer, Zero Trust-principes en de AI-beveiligingsperimeter binnen Microsoft 365 uit te leggen. Gevoelige informatie te beveiligen met behulp van Microsoft Purview Information Protection en Sensitivity Labels. Risico's van het te veel delen van gegevens in SharePoint en OneDrive te identificeren en te beperken om het gegevensbeheer te verbeteren. Data Security Posture Management (DSPM) voor AI implementeren om de beveiliging en compliance te versterken. Begrijp Microsoft 365 Agents, hun levenscyclus, governance en best practices voor beheer. Configureer Microsoft 365 Copilot, inclusief licentievereisten en essentiële beheerinstellingen. Breid de mogelijkheden van Copilot uit met behulp van Copilot Studio, aanpassingen en technieken voor het afstemmen van modellen. Pas de concepten van Microsoft 365 Copilot toe aan de hand van praktische scenario's en bereid je vol vertrouwen voor op het AB-900-certificeringsexamen. * Microsoft 365 Copilot: de M365-architectuur en de basis van Copilot * Microsoft 365 Copilot: identiteit, Zero Trust en de AI-perimeter * Microsoft 365 Copilot: Microsoft Purview-informatiebescherming en gevoeligheidslabels * Microsoft 365 Copilot: het beperken van het overmatig delen van gegevens in SharePoint en OneDrive * Microsoft 365 Copilot: Data Security Posture Management (DSPM) voor AI * Microsoft 365 Copilot: Microsoft Agent 365 en levenscyclusbeheer * Microsoft 365 Copilot: Copilot-licenties en kernconfiguratie * Microsoft 365 Copilot: uitbreidbaarheid, Copilot Studio en modelafstemming * Microsoft 365 Copilot: Voorbereiding op het examen en afsluitende oefenopdracht OCICT biedt flexibele maatwerktrainingen, individueel of klassikaal. Op basis van klantbehoefte creëren we leertrajecten met directe toepasbaarheid, afgestemd op leerstijl en (leer)doelstellingen. Theorie en praktijk wisselen elkaar continu af, en de inhoud is vooraf én tijdens de training aanpasbaar.De OCICT maatwerk-methode houdt in dat op basis van de behoefte van de klant - en indien nodig na een intakegesprek - een individueel opleidingstraject wordt opgesteld. De trainingen worden veelal individueel gevolgd, zodat iedere training een maatwerktraject is. Klassikale trainingen zijn natuurlijk mogelijk, mits ze aansluiten bij de leerbehoeften van de deelnemers / opdrachtgever.\nAlle onderdelen van de training kennen een voortdurende wisselwerking tussen theorie en praktijk. De inhoud van de training kan vooraf per cursist worden aangepast en tijdens de cursus worden bijgesteld. De focus ligt op maatwerk: het traject wordt afgestemd op de doelstellingen van de deelnemer(s) en/of opdrachtgever, ongeacht of het individueel of klassikaal wordt aangeboden.