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There are 4 modules in this course
Dive into the transformative world of generative AI with Microsoft Azure! This course is your hands-on introduction to building intelligent applications, taking you from core concepts to completing multiple hands-on projects. You will start by understanding the fundamentals of what makes generative AI unique and explore its evolution from traditional AI models to the generative approach.
Next, you'll get acquainted with the Azure AI Foundry, Microsoft's powerful platform for AI development. Through practical labs and activities, you will learn to set up your environment, experiment with different AI models, and configure key parameters. The course culminates in you designing, building, and refining your own text generation application. Crucially, you will also learn to integrate essential ethical principles, ensuring your AI solutions are responsible and safe. By the end, you won't just understand generative AI; you'll have the practical skills to build with it.
This foundational module sets the stage for your journey into generative AI. We begin by exploring the "why" behind this revolutionary technology and demystifying core concepts like Artificial Intelligence, Machine Learning, and Deep Learning. You will learn the crucial distinction between generative models, which create new content, and discriminative models, which classify existing data. To provide context, we will also trace the evolution of AI architectures, highlighting the key milestones that led to today's advanced systems. By the end of this module, you'll have a solid conceptual foundation, ready to dive into the practical tools in the next section.Important Notice on the Azure Interface: The screencast videos and screenshots were last updated in late 2025. Please be aware that Microsoft may have updated the Azure interface since then. If the steps shown in the course materials look different from your current Azure environment, please follow the most up-to-date interface, as the underlying concepts and learning objectives remain the same.
What's included
6 videos4 readings4 assignments
Show info about module content
6 videos•Total 29 minutes
Introduction to Microsoft Generative AI Engineering certification•4 minutes
Introduction to getting started with generative AI in Azure course•4 minutes
Why generative AI matters•6 minutes
Generative vs. Discriminative models in action•6 minutes
AI architecture developments•5 minutes
Module 1 summary: from core concepts to AI's evolution•3 minutes
4 readings•Total 30 minutes
Course syllabus and recommended background•5 minutes
Decoding the AI landscape: AI, machine learning, and deep learning•5 minutes
Comparing generative and discriminative models•10 minutes
Understanding AI evolution milestones•10 minutes
4 assignments•Total 120 minutes
Module 1 evaluation: Generative AI fundamentals: Graded Quiz•30 minutes
Exploring Generative and Discriminative AI•30 minutes
Foundational AI concepts quiz: Practice Quiz•30 minutes
AI architecture understanding: Practice Quiz•30 minutes
Getting acquainted with Azure AI Foundry
Module 2•5 hours to complete
Module details
This module moves from theory to practice as you get hands-on with Microsoft's powerful suite of AI tools. You will be guided through setting up your own Azure AI Foundry environment, learning to navigate its key interfaces, and configuring different types of AI models. The core of this module is experimentation; you will run both predefined and custom experiments, learning to adjust critical parameters and observe how they influence model behavior. Through a series of practical labs, you will build confidence in using the platform's Chat-Playground and Python SDK, preparing you to build real-world applications.
Important Notice on the Azure Interface: The screencast videos and screenshots were last updated in late 2025.
Please be aware that Microsoft may have updated the Azure interface since then. If the steps shown in the course materials look different from your current Azure environment, please follow the most up-to-date interface, as the underlying concepts and learning objectives remain the same.
What's included
6 videos4 readings7 assignments
Show info about module content
6 videos•Total 30 minutes
Module 2 introduction: from theory to practice with Azure AI Foundry•3 minutes
Discovering Azure AI tools•5 minutes
Navigating Azure AI Foundry: a quick guide•7 minutes
The Why and How of AI Experimentation•7 minutes
Running your first experiment in Azure AI•5 minutes
Module 2 summary: From setup to experimentation in Azure AI•3 minutes
4 readings•Total 40 minutes
Getting started with Azure AI Foundry•10 minutes
Azure AI Foundry: A quick reference guide•10 minutes
A guide to experimentation in Azure AI•10 minutes
Experimentation insights with Azure AI•10 minutes
7 assignments•Total 200 minutes
Module 2 evaluation: Graded Quiz•30 minutes
Setting up your Azure AI Foundry Project•30 minutes
Azure environment configuration and parameter testing•30 minutes
Azure AI Foundry basics: Practice Quiz•15 minutes
Running your first AI experiments•30 minutes
Advanced experimentation practice in Azure•35 minutes
Azure experimentation skills: Practice Quiz•30 minutes
Building your first AI application
Module 3•5 hours to complete
Module details
Now it's time to build! In this project-based module, you will apply your skills to construct a complete text generation application, focusing on the backend logic and AI integration. You will begin by designing the application's blueprint, outlining its core functionality and API design. A simple, pre-built user interface will be provided, allowing you to concentrate on the AI development. Then, you'll bring your application to life by integrating an Azure AI model and developing the necessary backend components. The final part of the module focuses on refinement; you will learn to test your application systematically, identify areas for improvement, and enhance its performance using techniques like prompt engineering and model fine-tuning. Optionally, you can explore customizing the provided UI, but the core focus will remain on building a functional and robust AI-powered application.
Important Notice on the Azure Interface: The screencast videos and screenshots were last updated in late 2025.
Please be aware that Microsoft may have updated the Azure interface since then. If the steps shown in the course materials look different from your current Azure environment, please follow the most up-to-date interface, as the underlying concepts and learning objectives remain the same.
What's included
4 videos7 readings5 assignments
Show info about module content
4 videos•Total 17 minutes
Blueprint of a text generation app•6 minutes
Setting the stage for your first AI application•4 minutes
Improving your AI application•4 minutes
Module 3 summary: from blueprint to a functional AI app•3 minutes
7 readings•Total 60 minutes
Choosing the right model for your application•5 minutes
Designing your application's API•5 minutes
Communicating with UI/UX and frontend teams•5 minutes
Framework design for text generation•10 minutes
Enhancing your AI application: From fine-tuning to deployment•15 minutes
Prioritizing AI application enhancements•10 minutes
Sample application enhancement and reflection•10 minutes
5 assignments•Total 210 minutes
Module 3 evaluation: Graded Quiz•30 minutes
Application framework construction•60 minutes
Application design knowledge: Practice Quiz•30 minutes
Enhancing application features•60 minutes
AI application testing and enhancement: Practice Quiz•30 minutes
Ethical AI usage and project completion
Module 4•4 hours to complete
Module details
Building powerful AI is only half the story; building it responsibly is essential. This final module focuses on integrating ethical principles and safety measures directly into your work. You will learn to identify and mitigate potential harms like bias and harmful content generation. We'll explore techniques like creating an ethical checklist and implementing Foundry's built-in safety features, such as content filters and prompt injection defenses. You'll learn how these safeguards protect your application from security risks and unwanted behaviors. While some controlled prompt modification can be useful in specific advanced scenarios, this course focuses on establishing a secure foundation. To conclude the course, you will complete a final hands-on project that brings everything together: enhancing your text generation application, integrating these critical ethical safeguards, and creating comprehensive documentation to showcase a solution that is both technically sound and ethically responsible.
Important Notice on the Azure Interface: The screencast videos and screenshots were last updated in late 2025.
Please be aware that Microsoft may have updated the Azure interface since then. If the steps shown in the course materials look different from your current Azure environment, please follow the most up-to-date interface, as the underlying concepts and learning objectives remain the same.
What's included
4 videos7 readings5 assignments
Show info about module content
4 videos•Total 16 minutes
Embedding ethics in AI•4 minutes
Introducing Azure's responsible AI toolkit•6 minutes
Final project lab walkthrough•4 minutes
Course summary •2 minutes
7 readings•Total 70 minutes
Guidelines for responsible AI use•10 minutes
Understanding bias and hallucinations in generative AI•10 minutes
Creating an ethical AI framework•10 minutes
Implementing ethical safeguards•10 minutes
Final project brief and success criteria•10 minutes
Final project: Responsible text generation app•10 minutes
Sample project solution, reflection, and next steps•10 minutes
5 assignments•Total 180 minutes
Text generation app assessment: Graded Quiz•30 minutes
Implementing responsible AI in practice•30 minutes
Ethical AI implementation skills: Practice Quiz•30 minutes
Documenting responsible AI practices•60 minutes
Ethical considerations in AI development: Practice Quiz•30 minutes
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