What you'll learn:
- End to End Solution Development, Deployment, Monitoring Features in Azure AI Foundry
- Learn Azure AI Services: Speech, Text to Speech, Language Translation, Vision and Document Service
- Developing a Retrieval Augmented Generation (RAG) Solution
- Azure AI foundry Ecosystem : Hub, Project, and Management Centre
- Monitoring and Tracing a deployed AI Model
- Configuring, Deploying AI Agents, Handoff, and Agent management practices
- Configuration, deployment of models and accessing via end points
- Safety and Security Features for an AI Solution
- Segregation of AI Models by Industry, Capability, License, Company
- Azure AI Foundry and Resources on Azure Cloud
- Concepts of Responsible AI
- Cost Considerations of an AI Solution
- Lifecycle of an AI Solution
- Testing the model capability in the Playground
Unlock the power of Artificial Intelligence in the cloud with this comprehensive, project-based tutorial on AI Development with Microsoft Azure AI Foundry. Whether you're an aspiring AI engineer, cloud developer, or a professional looking to upskill, this course will guide you through building, deploying, and managing real-world AI solutions end-to-end.
In this hands-on learning experience, you’ll explore the full Azure AI ecosystem and learn how to transform ideas into production-ready AI applications.
What You Will Learn:
• End-to-End AI Solution Development — From ideation to deployment, monitoring, and lifecycle management.
• Navigating Azure AI Foundry — Master the platform’s interface, tools, and capabilities including Hubs, Projects, and the Management Centre.
• RAG (Retrieval-Augmented Generation) — Build intelligent solutions that blend LLMs with enterprise data for improved accuracy.
• Azure AI Agents — Learn configuration, deployment, handoff workflows, and agent management best practices.
• Model Deployment & Endpoint Integration — Configure and deploy AI models, access them via endpoints, and test them in the Azure Playground.
• Monitoring, Tracing & Observability — Track model performance, diagnose issues, and ensure operational excellence post-deployment.
• Azure AI Services — Deep dive into Speech, Text-to-Speech, Vision, Document Intelligence, and Translation services.
• Safety, Security & Responsible AI — Apply responsible AI principles and implement guardrails to build secure, ethical AI applications.
• AI Model Segregation — Organize models by industry, capability, license, and provider for optimized solution design.
• Cost Planning & Optimization — Understand pricing, consumption, and cost considerations for scalable AI solutions.
• AI Solution Lifecycle Management — Gain clarity on building sustainable, maintainable AI systems from start to finish.
Why This Course Stands Out:
Project-based learning that ensures real-world readiness
Clear explanations for both beginners and experienced professionals
Focus on production-grade AI development, not just experimentation
Full coverage of the Azure AI Foundry ecosystem and modern AI practices
Practical insights on deploying, monitoring, and scaling AI solutions
By the end of this tutorial, you’ll be fully equipped to design robust AI architectures, deploy intelligent models, integrate Azure AI services, and manage complete solutions with confidence.
If you’re ready to build powerful AI applications in the cloud—this course is your roadmap. Enroll now and start your journey into Azure-powered AI innovation!
Disclaimer:
This course is for educational purposes only. Any practical implementation of AI models and services should be conducted with due diligence and in compliance with ethical and regulatory guidelines. This tutorial does not serve as a real-time implementation guide.
