Microsoft Azure is a public cloud computing platform that offers a variety of services, including compute, analytics, storage, and networking. Businesses can use these services to build and scale new applications or run existing ones in the cloud. Azure helps organizations meet their goals by offering tools that support various industries, such as e-commerce and finance. It's compatible with open-source technologies, giving users the flexibility to work with their preferred tools.

Azure provides four types of cloud computing models: infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS), and serverless computing. With its wide range of services, Azure is used for diverse purposes, including running virtual machines or containers to host infrastructure components like DNS servers, Windows Server services (such as IIS), or third-party applications. Azure also supports operating systems like Linux.

Another common use of Azure is hosting databases in the cloud. It offers serverless relational databases like Azure SQL and non-relational options such as NoSQL. Additionally, many organizations use Azure for backup, disaster recovery, and long-term data storage to meet retention requirements.

• In-Demand Technical Edge: Moves beyond generic AI theory by giving you real, resume-building experience with the modern Microsoft Foundry SDK.
• Official Microsoft Validation: Directly aligns with the AI-901 exam objectives, giving you a clear pathway to a universally recognized cloud credential.
• Career Future-Proofing: Bridges the gap between non-technical roles and AI engineering, making you highly valuable to teams adopting cloud-based automation.
• Hands-On Capability: You won't just talk about AI—you will finish the course knowing how to write basic Python code to deploy functional AI agents and text apps.
• Practical Business Value: Equips you to significantly reduce manual labor in your organization by setting up automated form processing and text summarization systems.

The Microsoft Certified: Azure AI Fundamentals (AI-901) training program is a foundational-level course designed to help learners understand core Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) concepts with a focus on Microsoft Azure services, Python coding foundations, and real-world implementation.

This course prepares participants to confidently identify AI use cases, understand foundation models, apply prompt engineering techniques, and build lightweight client applications using Microsoft Foundry, Azure Speech, and Azure Content Understanding.

Aligned with the official Microsoft exam guide, this program emphasizes a blend of conceptual AI understanding and foundational technical skills, including basic Python syntax and Azure resource interaction.

Skills Covered

You will:

• Responsible AI Principles: Evaluating solutions for fairness, safety, privacy, inclusivity, transparency, and accountability.
• Model Configuration: Setting parameters and choosing deployment options for generative and foundation models.
• Prompt Engineering: Designing effective system and user prompts for complex multimodal interactions.
• SDK Application Development: Writing lightweight Python client applications using the Microsoft Foundry SDK.
• AI Agent Design: Building, testing, and deploying single-agent solutions and automated AI workflows.
• Natural Language Processing (NLP): Implementing sentiment analysis, entity detection, and keyword extraction.
• Speech &Audio Integration: Developing applications utilizing automated speech recognition and speech synthesis.
• Computer Vision: Processing visual inputs and generating new visual outputs using generative image models.
• Advanced Information Extraction: Utilizing Azure Content Understanding to pull structured data from forms, documents, video, and audio.

Prerequisites:

There are no mandatory prerequisites for this course. However, basic familiarity with cloud concepts, programming fundamentals, and data concepts will help students progress more quickly through the intermediate modules.

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‍What is Microsoft Azure AI Fundamentals(AI-901)?

The Microsoft Azure AI Fundamentals (AI-901) course is a newly updated, foundational-level training program tailored for individuals entering the field of artificial intelligence on the cloud. It introduces core machine learning, computer vision, natural language processing, and generative AI concepts specifically within the Microsoft ecosystem. Unlike older fundamental tracks, this course explicitly emphasizes hands-on implementation using the advanced Microsoft Foundry portal and SDK. Participants will learn how artificial intelligence models process data, generate text, and evaluate images through multimodal systems. The program strongly highlights Microsoft's six pillars of Responsible AI to ensure ethical application deployment. Additionally, it bridges the gap between pure business concepts and basic technical delivery by incorporating foundational Python coding syntax. Students will discover how to orchestrate automated single-agent workflows to streamline modern corporate tasks. Ultimately, it serves as the essential stepping stone for passing the official AI-901 certification exam. By completing this track, learners prove their readiness to build, deploy, and manage lightweight, modern AI solutions on Azure.

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Who Should Attend:

• Aspiring AI Engineers
• Data Scientists and ML Engineers
• Cloud Developers and Architects
• Software Developers transitioning to AI
• IT professionals seeking Azure AI skills
• Beginners starting an AI/cloud career

Module 1: Identify AI Concepts and Capabilities (40–45%)

Topic:

• Principles of Responsible AI: Fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.
• AI Model Components: How generative AI models work, identifying models based on capabilities, deployment options, and configuration parameters.
• AI Workloads& Scenarios: Generative and agentic AI, text analysis, speech, computer vision, and information extraction.
• Text Analysis& Speech Techniques: Keyword extraction, entity detection, sentiment analysis, summarization, speech recognition, and speech synthesis.
• Vision & Extraction Techniques: Computer vision, image-generation models, and information extraction from text, audio, images, and videos

Lab:

• Exploring Microsoft Foundry portal and Azure AI services overview
• Analyzing Responsible AI case studies

Module 2: Implement Generative AI Apps and Agents (15–20%)

Topic:

• Designing effective system and user prompts for generative AI models
• Deploying foundation models and configuring parameters in Microsoft Foundry
• Introduction to the Microsoft Foundry SDK for application development
• Building single-agent solutions and configuring agentic workflows

Lab:

• Hands-on prompt engineering and model deployment in Foundry
• Building alight weight chat client application using Python and the Foundry SDK
• Creating and testing a single-agent solution in the Foundry portal

Module 3: Implement Text and Speech Solutions (12–15%)

Topic:

• Developing text analysis features in client applications
• Multimodal model interactions with speech and text inputs
• Utilizing Azure Speech capabilities within Foundry Tools

Lab:

• Building alight weight application that includes automated text analysis
• Designing an application to respond to spoken prompts using a deployed multimodal model
• Setting up Azure Speech integration in a client application

Module 4: Implement Computer Vision and Image-Generation (12–15%)

Topic:

• Interpreting visual inputs (images/video) using multimodal prompts
• Generating new visual outputs using AI image-generation models
• Integrating vision capabilities into developer workflows

Lab:

• Creating visual outputs from text prompts using generative vision models
• Building a lightweight Python application with vision capabilities using Microsoft Foundry

Module 5: Implement Information Extraction with Content Understanding (12–15%)

Topic:

• Introduction to Azure Content Understanding within Foundry Tools
• Extracting structured data from unstructured forms, documents, and images
• Extracting insights and metadata from audio and video files

Lab:

• Document and form processing using Content Understanding
• Building a lightweight client application with advanced information extraction capabilities

Key Microsoft Services Covered

• Microsoft Foundry (Portal & SDK)
• Azure Content Understanding
• Azure Speech Services
• Azure Computer Vision / Image-Generation Models
• Azure Machine Learning
• Language Understanding / NLP Tools
• Azure Bot Service & Agents
• Azure Resources & Resource Groups

Certification Exam Details

• Exam Code: AI-90
• Questions: ~40–60 questions
• Duration: ~45–60 minutes
• Format: MCQ, Multiple Response, Drag-and-Drop, Case Studies
• Passing Score: 700 / 1000
• Level: Foundational

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In this module, students will learn how to:

• How generative and agentic AI models function, deploy, and scale within cloud environments.
• The exact steps to build and test single-agent AI systems inside the Microsoft Foundry portal.
• Techniques for crafting robust system and user prompts to maximize the accuracy of LLMs.
• How to write basic Python client applications that seamlessly interact with the Microsoft Foundry SDK.
• Methods to analyze text for sentiment, extract key phrases, and embed speech recognition into apps.
• How to configure computer vision models to interpret visual prompts and generate high-quality images.
• Ways to automate data entry by extracting text and intelligence from documents using Content Understanding.
• How to structure cloud workflows that process multi-format inputs, including images, audio, and videos.
• Strategies to align every AI project with corporate compliance, security, and ethics frameworks.