SC-500: Implement end-to-end security controls for cloud and AI workloads

Price
Net: €
VAT: €

Price
Price on Request

Duration
4 days

For companies and job seekers:
this course is 100% fundable!

Location

Course Language
English

Training Solutions
Online Live

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Cloud platforms, AI applications, and hybrid infrastructures create new attack vectors that quickly push traditional security approaches to their limits. What’s needed are end-to-end protection mechanisms that jointly secure identities, data, networks, and workloads. The focus is on modern security architectures for Microsoft Azure, AI services, and cloud-based applications.

Key Topics

Security controls for cloud and AI workloads
Zero Trust concepts in Azure environments
Identity and access management with Microsoft Entra ID
Network segmentation and secure communication between services
Protection of Sensitive Data Through Encryption and Policies
Monitoring, threat detection, and security monitoring
Governance and Compliance Requirements in Cloud Environments

Prerequisites
In-depth knowledge of Microsoft Azure and identity management, as well as basic experience with cybersecurity, networks, and cloud technologies.

Target Audience
Security engineers, cloud architects, Azure administrators, cybersecurity managers, and professionals responsible for AI and cloud security.

Modern security strategies are no longer developed in isolation for each individual system or application. Successful security concepts integrate identities, data, infrastructure, and AI services into a holistic security architecture with high resilience.

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Course Content

Accessing Resources with Microsoft Entra

Authentication with Microsoft Entra ID
Privileged Identity Management (PIM)
API Authentication for Declarative Agents

Azure Key Vault for Cloud and AI Security

Configuring and Securing Azure Key Vault
Managing Keys and Secrets
Certificate Management and Monitoring
Protection with Microsoft Defender for Cloud

Security Governance and Compliance

Governance with Azure Policy and Resource Locks
Security controls in Microsoft Defender for Cloud
Compliance and Regulatory Requirements
RBAC roles based on the principle of least privilege
Backing up data with Azure Backup
Security controls in Infrastructure as Code

Azure Storage for Cloud and AI Workloads

Understanding Azure Storage
Securing Access to Azure Storage
Network Protection for Azure Storage
Using Microsoft Defender for Storage

Securing Azure SQL Databases

Security Features for Azure SQL
Logging and Monitoring
Microsoft Defender for Databases

Network Security Measures in Azure

Network Segmentation in Azure
Deploying Azure Firewall
Remote and Hybrid Access
Public Access to PaaS Services

Security for AI

Securing Microsoft Entra Agent Identity
Analyze AI Identity Risks
Protect Copilot Studio agents
Configure security for AI Gateway
Manage security boundaries in Microsoft Foundry
Protect AI workloads with Defender for Cloud
Enable Defender for AI Services
Manage agents with Microsoft Agent 365
Manage AI data risks with Microsoft Purview

Security for Servers and Virtual Machines

Hard Drive Encryption for VMs
Trusted Launch for Azure VMs
Deploying Azure Bastion
Securing Hybrid Servers
Implement Defender for Server
Controlling Just-in-Time Access
Security Policies for VMs

Secure Azure Application Platform Services

Securing Azure App Service
Securing Azure Functions
Securing Azure Container Apps
Securing Azure Kubernetes Service (AKS)
Protecting Azure API Management
Securing Azure Logic Apps
Securing Azure Event Grid
Protecting Azure Service Bus
Securing Azure Storage services

Security Status with Microsoft Defender for Cloud

Defender for Cloud Features
Monitor Security Status
Enable advanced protection features
Implement security recommendations
Meet compliance requirements

Activity and Event Logging with Microsoft Sentinel

Capturing Windows Events
Collect Linux events
Connect Azure resources
Integrate Microsoft 365
Connect Defender for Endpoint
Connect Defender for Identity
Integrate Defender for Office 365
Configure third-party data sources

Deployment and Operation of Microsoft Security Copilot

Deploy Security Copilot
Operating Security Copilot
Extend Security Copilot
Integration with Microsoft Sentinel
Integration with Microsoft Defender XDR
Integration with Microsoft Intune
Integration with Microsoft Purview

Your training will be 100% funded

Our funding schemes are available exclusively to participants who live or work in Germany. Funding is not available outside Germany.

For career starters, job seekers, career changers, startups, experienced professionals, those looking to advance their careers, specialists, etc.

The QCG program for everyone in the company

Further information

The education voucher for all job seekers

Further information

Frequently Asked Questions

Who is this topic relevant to?

This expertise is particularly in demand among security engineers, cloud architects, IT administrators, and SOC teams. Areas such as compliance, data protection, and governance also benefit from a better understanding of identities, permissions, and security policies in cloud and AI environments.

What knowledge is required?

A solid foundation in Microsoft Azure, cloud technologies, and IT security makes it much easier to get started. Knowledge of identities, role-based models, and multi-factor authentication is helpful, as these concepts play a central role in modern security architectures.

Which Microsoft tools are used?

Microsoft Entra ID, Microsoft Defender, Microsoft Sentinel, Microsoft Purview, and Azure Key Vault are frequently used. These solutions support identity protection, threat detection, data classification, compliance, and the monitoring of security-related events.

Where are these solutions used?

Typical use cases include Microsoft 365, Azure, hybrid infrastructures, and AI platforms. Security controls protect identities, data, applications, and interfaces across various systems and services.

What are the day-to-day tasks?

Typical responsibilities include managing permissions, implementing security policies, and analyzing security incidents. Securing new cloud services and AI applications is also increasingly part of day-to-day operations.

Why is AI security important?

AI systems often process sensitive corporate data and access internal information. This gives rise to new risks, such as data leakage, excessive permissions, or manipulated inputs, which require additional security measures.

What are the professional benefits?

Knowledge of cloud security and AI security is among the most in-demand skills in the cybersecurity market. In particular, the combination of security architecture, compliance, and AI governance is becoming increasingly important in companies.

What security strategies are considered best practices?

Zero Trust, multi-factor authentication, and role-based access are among the most important security strategies today. They are complemented by encryption, monitoring, and regular reviews of permissions and policies.

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