Azure Fundamentals with AI Integration Training is a practical course designed to introduce learners to core Microsoft Azure concepts while building awareness of how AI and machine learning are integrated into the Azure ecosystem. The course starts with Azure fundamentals such as subscriptions, resource management, virtual machines, storage, and security, providing a solid cloud foundation.

Learners then explore essential AI and machine learning concepts and understand how Azure supports AI workloads through services such as Azure AI, Azure Machine Learning Compute, GPU-enabled infrastructure, and Azure Kubernetes Service (AKS). The course focuses on how AI solutions are hosted, managed, and scaled on Azure rather than deep model development.

By the end of the course, learners will understand how Azure cloud services and AI capabilities work together, preparing them for cloud-based AI projects and serving as a strong bridge between AZ-900 Azure Fundamentals and more advanced AI or data science training such as DP-100 Data Science on Azure.

Module 1: Getting Started with Cloud and Azure

• What is cloud computing and why it matters

• Introduction to Microsoft Azure

• Managing Azure resources

• Subscription management, support, and billing

• Customizing the Azure Portal interface

• Viewing billing, usage, and quota information

• Overview of virtual machines in Microsoft Azure

Module 2: Creating and Configuring Azure Virtual Machines

• Introduction to Azure Virtual Machines

• Creating a virtual machine using Azure Marketplace images

• Configuring VM compute and storage options

• Verifying VM functionality and access

• Managing and monitoring virtual machines

• Best practices for VM configuration

Module 3: Exploring Azure Storage and Databases

• Overview of Azure Storage services

• Understanding Azure Blob Storage for data storage

• Using Azure File Storage for data sharing

• Overview of relational database options in Azure

• Creating and connecting to Azure SQL Databases

• Creating and configuring Azure Storage accounts

Module 4: Security and Compliance in Azure

• Introduction to Azure security concepts

• Azure security features and best practices

• Overview of Azure Active Directory (Azure AD)

• Identity and access management fundamentals

• Understanding compliance tools and standards in Azure

Module 5: Introduction to AI and Machine Learning

• What is Artificial Intelligence (AI)?

• What is Machine Learning (ML)?

• Differences between AI and ML

• Historical evolution and milestones in AI and ML

• Supervised, unsupervised, and reinforcement learning

• Understanding training, testing, and validation data

Module 6: Introduction to Azure AI

• What is Azure AI and its role in cloud solutions

• Benefits of using Azure AI services

• Azure AI vs other AI platforms

• Overview of Azure AI services and capabilities

• Getting started with Azure AI solutions

Module 7: Azure AI Infrastructure and Compute

• Understanding GPU-enabled virtual machines

• AI model training infrastructure on Azure

• Introduction to Azure Machine Learning Compute

• Using Azure Kubernetes Service (AKS) for AI workloads

• Scaling and managing AI infrastructure on Azure

Module 8: Integrating Azure Fundamentals with AI Workloads

• How Azure core services support AI solutions

• Combining storage, compute, and networking for AI use cases

• Security considerations for AI workloads

• Monitoring and managing AI infrastructure

• Real-world examples of Azure-based AI solutions

Module 9: Assignments and Hands-On Practice

• Guided hands-on exercises using Azure Portal

• Practical labs covering VMs, storage, and security

• Conceptual exercises for Azure AI services

• Reinforcement through assignments and review

• Q&A and recap sessions

To successfully complete Azure Fundamentals with AI Integration Training, learners should have:

• Basic computer literacy and comfort using a computer

• No prior experience with Microsoft Azure or cloud computing required

• No programming or machine learning background required

• Interest in learning cloud technologies and AI concepts

• Willingness to participate in hands-on demonstrations and assignments

By the end of this course, you will be able to:

• Understand core cloud computing concepts and Microsoft Azure fundamentals

• Navigate and manage resources using the Azure Portal

• Create and configure Azure Virtual Machines and basic storage services

• Understand Azure Storage and database options for cloud applications

• Apply basic security, identity, and compliance concepts in Azure

• Explain key Artificial Intelligence and Machine Learning concepts

• Understand how Azure AI services support AI-driven solutions

• Identify infrastructure options for AI workloads, including GPU instances and AKS

• Understand the role of Azure Machine Learning Compute in scalable training

• Integrate Azure fundamentals with AI and ML workloads

• Recognize common Azure-based AI use cases

• Build a strong foundation for progressing to advanced Azure, AI, or data science training

This course prepares learners for foundational and early-career roles that combine cloud computing knowledge with AI awareness. After completing the training, learners will be better prepared for positions such as:

• Cloud Support Associate

• Junior Cloud Engineer

• Azure Cloud Associate

• Cloud Operations Analyst

• AI Support Engineer (Entry-Level)

• IT Support Specialist (Cloud & AI)

• Cloud Technology Associate

• Junior AI Infrastructure Engineer

• Cloud Systems Support Analyst

• Technical Support Engineer (Azure & AI)