IT and Infrastructure Training Course


Practical configuration and deployment training for IT teams managing
AI rollout within enterprise security constraints.

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Enterprise Microsoft Copilot Deployment

1 days, classroom/online
Next course 17 Aug, London, £2,500.00+VAT
Onsite courses available on request

MLOps: AI Deployment Pipeline

1 days, classroom/online
Next course 17 Aug, London, £2,500.00+VAT
Onsite courses available on request

AI Governance Tooling

1 days, classroom/online
Next course 17 Aug, London, £2,500.00+VAT
Onsite courses available on request

What is IT & Infrastructure AI Training?

IT and infrastructure teams are responsible for securely deploying, integrating, and managing AI technologies across the enterprise. As organisations adopt Microsoft Copilot, generative AI platforms, AI agents, and cloud AI services, infrastructure professionals must understand how to configure environments, secure data, manage identities, and ensure AI solutions operate reliably within existing enterprise architecture.

JBI's IT & Infrastructure AI courses cover the complete deployment lifecycle: from AI platform architecture and Microsoft 365 readiness, through identity, security, networking, governance, and infrastructure planning, to advanced topics including Azure AI services, AI operations (AIOps), monitoring, compliance, and enterprise-scale deployment. Whether you are preparing your organisation for Microsoft Copilot, integrating AI services into existing infrastructure, or managing AI platforms in production, we offer courses matched to your role and technical experience.

All courses are delivered by experienced infrastructure practitioners who deploy enterprise AI solutions professionally. Training is available as instructor-led online live sessions or onsite at your UK premises, and every programme can be customised to your organisation's infrastructure, security policies, and technology stack.

Learning Outcomes – What You Will Learn

Core skills and competencies gained across our IT & Infrastructure AI training programmes.

✓ Prepare enterprise infrastructure for secure AI deployment

✓ Configure Microsoft 365, Azure, and identity services to support AI workloads

✓ Implement governance, compliance, and data protection for enterprise AI

✓ Deploy and manage Microsoft Copilot, Azure AI, and AI-enabled business services

✓ Secure AI environments using Microsoft Entra ID, Conditional Access, and Zero Trust principles

✓ Monitor AI services, optimise performance, and troubleshoot deployment issues

✓ Integrate AI platforms with existing enterprise systems and infrastructure

✓ Develop operational best practices for managing AI securely at enterprise scale

IT & Infrastructure AI Training for Every Role

Courses matched to your responsibilities and deployment requirements.

🖥️ IT Administrators

Configure Microsoft 365, Azure, identity services, licensing, and enterprise settings required to deploy AI solutions securely.

☁️ Infrastructure Engineers

Design and manage scalable infrastructure that supports AI services while maintaining availability, resilience, and performance.

🔐 Security & Identity Teams

Implement governance, access controls, data protection, compliance, and Zero Trust security for enterprise AI deployments.

⚙️ Systems Engineers

Integrate AI platforms with existing enterprise applications, networking, storage, and infrastructure services.

📡 Cloud Engineers

Deploy and manage Azure AI services, cloud infrastructure, automation, monitoring, and operational best practices.

👔 IT Leaders & Infrastructure Managers

Develop AI deployment strategies, infrastructure roadmaps, governance frameworks, and operational models that support secure enterprise adoption.

What Delegates Say – Testimonials

★★★★★
"Exactly the practical deployment guidance our infrastructure team needed before rolling out Microsoft Copilot. We left with a clear implementation plan and governance checklist."

IT Infrastructure Manager
Financial Services, London

★★★★★
"The security and identity sections were particularly valuable. The course explained not just how to configure AI services, but how to deploy them safely within our existing environment."

Cloud Engineer
Public Sector Organisation, Manchester

★★★★★
"A highly practical course with real-world labs rather than product demonstrations. It helped our team prepare Azure and Microsoft 365 for AI deployment with confidence."

Senior Systems Administrator
Technology Company, Birmingham

Training Delivery Options

🖥️ Online Live Training

Instructor-led interactive sessions delivered remotely. Hands-on configuration labs, guided deployment exercises, and expert instructors.

📍 London Classroom

Attend scheduled public courses at our London training centre and gain practical deployment experience alongside other IT professionals.

🏢 Onsite at Your Premises

We deliver training at your offices. Ideal for IT teams preparing for AI implementation. Courses can be customised around your infrastructure, security model, and technology estate.

🎯 Bespoke Corporate Programmes

Tailored AI infrastructure and deployment programmes designed around your organisation's architecture, governance requirements, security standards, and AI adoption roadmap.

FAQs

JBI Training offers three specialist IT and Infrastructure AI courses designed for enterprise IT teams managing AI deployment. Available courses are Enterprise Microsoft Copilot Deployment (one day), MLOps: AI Deployment Pipeline (one day), and AI Governance Tooling (one day). All courses are available as scheduled classroom sessions in London, as live online instructor-led training, or as customised onsite programmes delivered at your organisation's premises. Each course can be tailored to your organisation's specific infrastructure, security policies, and technology stack.
The courses are designed specifically for IT professionals who are responsible for deploying, integrating, securing, and managing AI technologies within an enterprise environment — rather than for end users or data scientists. This includes IT administrators configuring Microsoft 365, Azure, and identity services for AI workloads; infrastructure engineers designing scalable environments to support AI services; security and identity teams implementing governance, access controls, and Zero Trust principles for AI deployments; systems engineers integrating AI platforms with existing enterprise applications and infrastructure; cloud engineers deploying and managing Azure AI services; and IT leaders and infrastructure managers developing AI deployment strategies and governance frameworks.
The Enterprise Microsoft Copilot Deployment course is a one-day practical programme for IT administrators and infrastructure professionals responsible for deploying Microsoft 365 Copilot across an organisation. It covers Microsoft 365 readiness assessment and configuration, identity and access management using Microsoft Entra ID, licensing management and user entitlement, data governance and sensitivity labelling to control what Copilot can access, security and compliance configuration, network and connectivity requirements, and planning and executing a phased Copilot rollout. The course focuses on the practical configuration and deployment steps rather than on end-user productivity features, and is delivered by experienced infrastructure practitioners who deploy enterprise AI solutions professionally.
MLOps (Machine Learning Operations) is the discipline of deploying, managing, monitoring, and maintaining machine learning models and AI systems in production environments — applying DevOps principles to the AI and machine learning lifecycle. JBI's one-day MLOps: AI Deployment Pipeline course covers the end-to-end AI deployment lifecycle from an infrastructure and operations perspective, including AI model packaging and containerisation, deployment pipeline design and automation, integrating AI workloads with CI/CD toolchains, infrastructure requirements for running AI models at scale, monitoring model performance and data drift in production, and incident response and operational best practices for AI systems. It is suited to infrastructure engineers, cloud engineers, and systems engineers who are responsible for the operational reliability of AI services in production.
The AI Governance Tooling course is a one-day programme covering the tools, frameworks, and technical controls used to govern AI systems within an enterprise. It covers AI governance requirements from a regulatory and organisational policy perspective, technical tooling for implementing governance controls — including audit logging, model explainability tools, bias detection, and access control frameworks — data protection and compliance requirements for AI workloads, integrating governance tooling into AI deployment pipelines, and monitoring and reporting on AI system behaviour to satisfy internal and external governance obligations. It is relevant for security teams, compliance professionals, IT managers, and infrastructure architects who need to ensure AI systems operate safely, transparently, and in accordance with regulatory requirements.
Zero Trust is a security model based on the principle of never implicitly trusting any user, device, or network — even those inside the corporate perimeter — and instead continuously verifying identity and authorising access based on the minimum permissions required for each specific action. It is particularly relevant to enterprise AI deployment because AI tools such as Microsoft Copilot access sensitive organisational data across Microsoft 365, SharePoint, Teams, and connected services. Without proper Zero Trust controls — including Microsoft Entra ID configuration, Conditional Access policies, sensitivity labelling, and data loss prevention — AI tools can inadvertently expose data to users who should not have access to it. JBI's Enterprise Microsoft Copilot Deployment course covers how to apply Zero Trust principles specifically to enterprise AI deployment.
Licensing Microsoft Copilot gives an organisation the right to use the product, but does not automatically make it ready for safe, effective enterprise deployment. A proper deployment involves assessing and configuring the Microsoft 365 environment to ensure data is correctly classified and protected before Copilot can access it, setting up identity and access controls so that Copilot respects existing permission boundaries, configuring governance and compliance policies, managing the rollout in phases to different user groups, and establishing monitoring and support processes. Organisations that skip the deployment and governance configuration stage and simply activate Copilot licences run the risk of exposing sensitive data, creating compliance issues, or delivering a poor user experience. JBI's Enterprise Microsoft Copilot Deployment course specifically addresses the gap between licensing and production-ready deployment.
JBI's IT and Infrastructure AI courses are complementary to, but entirely separate from, the end-user Microsoft Copilot training courses in JBI's curriculum. The end-user courses — such as Microsoft Copilot Essentials and Microsoft Copilot 365 Introduction — teach employees how to use Copilot productively for their daily work. The IT and Infrastructure courses teach IT teams how to prepare, configure, secure, deploy, and govern the underlying environment that makes Copilot work safely across the organisation. A successful enterprise Copilot rollout typically requires both streams of training — technical deployment skills for IT teams and adoption skills for end users.
Yes. Enterprise AI deployment is a rapidly evolving area and JBI's IT and Infrastructure AI course content is continuously reviewed and updated to reflect the latest Microsoft releases, platform changes, and regulatory developments. This includes updates to Microsoft 365 Copilot deployment requirements, changes to Microsoft Entra ID and Conditional Access capabilities, new Azure AI services and infrastructure options, evolving MLOps tooling and best practices, and the latest guidance from Microsoft and regulators on AI governance and compliance. Delegates learn practical skills that are directly applicable to the enterprise AI infrastructure landscape as it exists today.

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