Azure Fundamentals with AI Integration is a foundational course designed to introduce learners to core Microsoft Azure cloud concepts while demonstrating how Artificial Intelligence services are integrated into modern cloud solutions. This course helps learners understand not only what Azure offers, but how organizations use Azure and AI together to build scalable, intelligent, and secure applications. 

The course begins with essential Azure fundamentals, including cloud computing concepts, core Azure services, pricing models, and security basics. As learners build this foundation, they are gradually introduced to Azure AI services—such as cognitive services, machine learning capabilities, and AI-powered tools—that enhance data processing, automation, and decision-making in cloud environments. 

Through guided demonstrations, real-world examples, and practical discussions, learners will explore how Azure supports AI-driven workloads across business, analytics, and application development use cases. The course emphasizes practical understanding over theory, enabling learners to confidently navigate the Azure ecosystem and recognize where AI fits within cloud architectures. 

By the end of the course, learners will have a clear understanding of Azure fundamentals, how AI services are integrated within Azure, and how organizations leverage cloud and AI together—providing a strong foundation for advanced Azure, AI, data, and cloud certification paths. 

This course is designed for beginners and early-career professionals who want to learn cloud fundamentals and understand how AI services integrate with Microsoft Azure. No prior Azure or AI experience is required. However, the following basic knowledge will be helpful: 

• Basic computer skills and familiarity with using web applications 

• General understanding of IT concepts, such as servers, storage, or networking (helpful but not mandatory) 

• Interest in cloud computing and AI technologies 

• Willingness to follow hands-on demonstrations using the Azure portal 

• Optional (but helpful): 

• Basic knowledge of Windows or Linux environments 

• Familiarity with databases or scripting concepts 

• Curiosity about cloud certifications such as Azure Fundamentals (AZ-900) 

This course is suitable for students, professionals, career changers, and anyone looking to build a strong foundation in Azure and AI-enabled cloud services. 

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

• Understand core cloud computing concepts and how Microsoft Azure delivers cloud services

• Navigate and manage resources using the Azure Portal

• Explain Azure subscription models, billing, usage, and quotas

• Create, configure, and verify Azure Virtual Machines

• Understand Azure storage services including Blob Storage and File Storage

• Create and connect to Azure SQL databases

• Apply security and identity management basics using Azure Active Directory

• Explain the fundamentals of Artificial Intelligence and Machine Learning

• Differentiate between AI and ML and understand common learning approaches

• Identify key Azure AI services and their business and technical benefits

• Understand how AI workloads are deployed using Azure AI infrastructure

• Recognize how GPU instances, AKS, and Azure Machine Learning Compute support AI solutions

• Build a strong foundation for advanced Azure, AI, and cloud certification paths

Learning Azure fundamentals with AI integration prepares learners for a range of beginner-level cloud, IT, and AI-enabled roles. After

completing this course, learners will be better prepared for positions such as:

• Cloud Support Associate / Cloud Support Engineer (Entry-Level)

• Azure Administrator (Junior / Associate Level)

• Cloud Operations Analyst

• IT Support Analyst (Cloud & Azure Environment)

• Junior Cloud Engineer

• AI Cloud Support Specialist

• DevOps Support Associate (Azure-focused)

• Systems Administrator (Cloud-based environments)

• Technical Support Engineer (Azure Services)

• Cloud & AI Solutions Assistant

Module 1: Getting Started with Cloud & Azure

• What is cloud computing?

• What is 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

• Understanding Azure VM components

• Creating a virtual machine using the Azure Portal

• Using Azure Marketplace images

• Verifying VM functionality

• Configuring VM storage

• Managing and monitoring Azure virtual machines

Module 3: Exploring Azure Storage & Databases

• Understanding Azure Blob Storage for data storage

• Using Azure File Storage for data sharing

• Overview of relational database deployment options in Azure

• Creating and connecting to Azure SQL databases

• Creating and configuring an Azure Storage account

Module 4: Security and Compliance in Azure

• Overview of Azure security features and tools

• Best practices for securing Azure resources

• Understanding compliance and governance in Azure

• Introduction to Azure Active Directory (Entra ID)

• Identity and access management basics

Module 5: Introduction to Artificial Intelligence & Machine Learning

• What are Artificial Intelligence and Machine Learning?

• Differences between AI and ML

• History and key milestones in AI and ML

• Types of Machine Learning:

• Supervised learning

• Unsupervised learning

• Reinforcement learning

• Training, testing, and validation datasets

Module 6: Introduction to Azure AI Services

• What is Azure AI?

• Benefits of using Azure AI services

• Azure AI vs. other AI platforms

• Getting started with Azure AI tools and services

• Overview of Azure Cognitive Services and AI capabilities

Module 7: Azure AI Infrastructure & Compute

• GPU-based virtual machines for AI workloads

• Training AI models using Azure infrastructure

• Azure Kubernetes Service (AKS) for containerized AI application

• Azure Machine Learning Compute for scalable model training