How is this program different from Azure AI certifications?

<text variant="body2">This program focuses on solution architecture skills. You will make and defend real architectural decisions, service selection, cost modeling, security design, governance, and deployment across the full Azure AI portfolio. The hands-on projects are designed to demonstrate job-ready competency to employers.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.

Microsoft Azure AI Solutions Architect Professional Certificate

Labor Day starts with $70+ in savings on Coursera Plus. Save 40% for 3 months.

Microsoft Azure AI Solutions Architect Professional Certificate

Design Enterprise AI on Azure.

Architect agentic, RAG, and multi-model AI solutions using Microsoft Foundry.

Instructors:

Included with Learn more

5 course series

Earn a career credential that demonstrates your expertise

Intermediate level

Recommended experience

Flexible schedule

Learn at your own pace

5 course series

Earn a career credential that demonstrates your expertise

Intermediate level

Recommended experience

Flexible schedule

Learn at your own pace

What you'll learn

Design and evaluate enterprise AI solution architectures using Microsoft Foundry and the Azure AI service portfolio.
Architect agentic and multi-agent AI systems with tool integration, memory, orchestration, and human-in-the-loop controls.
Apply security, governance, and responsible AI frameworks to Azure AI deployments across enterprise environments.
Design RAG, NLP, speech, vision, and knowledge mining solutions for real-world business scenarios.

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Advance your career with in-demand skills

Receive professional-level training from Microsoft
Demonstrate your technical proficiency
Earn an employer-recognized certificate from Microsoft

Professional Certificate - 5 course series

Go beyond learning Azure AI services to develop the architectural decision-making skills needed to design, evaluate, secure, and govern enterprise AI solutions. This program teaches you to design, evaluate, and govern enterprise AI systems using Microsoft Foundry, Azure OpenAI Service, and the full Azure AI portfolio from RAG pipelines and agentic workflows to NLP, speech, vision, and knowledge mining.

This program is designed for cloud architects, AI engineers, software developers, and technical consultants. Completion of this program will help learners target the roles of Azure AI Solutions Architect or AI Solutions Architect. Apply your skills across four real-world architecture projects and create portfolio-ready diagrams, design specifications, and solution documents.

You'll work through real-world scenarios in financial services, healthcare, legal, and enterprise IT, applying structured decision frameworks to select services, model costs, configure security, enforce governance, and operationalize AI at scale. Each long course targets a distinct architectural domain: platform foundations, core solution design, cognitive and knowledge services, and agentic systems with security, governance, and operations.

By the end of this program, you'll be equipped to lead AI architecture conversations, evaluate design trade-offs, and deliver solutions that meet enterprise standards for performance, compliance, and safety.

Applied Learning Project

Complete four architecture projects—one per long course—that mirror the work of a practicing Azure AI Solutions Architect. Projects include designing a Foundry workspace for a multinational enterprise, architecting a RAG solution for a 50,000-document knowledge base, building a cognitive and knowledge services architecture for an insurance claims platform, and designing a complete end-to-end agentic AI solution with security, governance, and observability. Each project produces a portfolio-ready architecture document, diagram, or design specification you can showcase to employers and clients.

Azure AI Foundations & Solution Planning

Course 1

What you'll learn

Map the Azure AI service portfolio and select appropriate services for enterprise solution scenarios.
Design a Microsoft Foundry workspace architecture with identity configuration and governance controls.
Analyze enterprise requirements against compliance constraints and model the cost of an Azure AI solution.
Apply build vs. buy vs. configure decision frameworks and token economics to solution planning.

Core AI Solution Design

Course 2

What you'll learn

Select Azure OpenAI models and design deployment configurations for multi-use-case enterprise environments.
Architect RAG solutions using Azure AI Search and Foundry IQ, including index design, chunking, and hybrid retrieval.
Design system prompt architectures and evaluation frameworks for AI quality, safety, and groundedness.
Evaluate fine-tuning, RAG, and prompt-only strategies, and design model routers for intelligent request routing.

Cognitive & Knowledge Services

Course 3

What you'll learn

Design NLP solutions using Azure AI Language and Translator for multilingual, conversational, and text analytics use cases.
Design computer vision and document intelligence solutions for enterprise image and document processing scenarios.
Architect speech solutions with real-time transcription, custom speech models, and multimodal Azure AI integration.
Design knowledge mining architectures using Azure AI Search enrichment pipelines and knowledge stores.

Agentic AI, Security, Governance & Operations

Course 4

What you'll learn

Design AI agents and multi-agent systems with tool integration, MCP connectivity, orchestration, and A2A protocols.
Design network security, identity controls, and prompt injection defenses for enterprise Azure AI deployments.
Design AI governance frameworks with unified access management, audit logging, and responsible AI controls.
Build and deploy production-ready AI solutions with CI/CD pipelines, observability, and end-to-end architecture.

Launch Your Azure AI Solutions Architect Career

Course 5

What you'll learn

Recognize the metacognitive diagnostic loop in your own past experiences with system failures and apply it to production architecture contexts
Connect the preemptive boundary analysis framework to real decisions you have made — and identify what would have surfaced hidden assumptions earlier
How platform drift insulation principles appear in contexts beyond software architecture & articulate how they apply to your own design decisions
Identify which of the 3 metacognitive capabilities you find most and least natural & use that self-knowledge to guide your professional development

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Microsoft

0 Courses0 learners

Microsoft

421 Courses2,848,368 learners

Offered by

Microsoft

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Break down barriers to learning with big savings
Get Coursera Plus
Start with easy savings for hard-working teams
Save 30% today

Frequently asked questions

AI engineers, cloud architects, and technical leads with foundational Azure and ML experience who are ready to advance into solution architecture roles. This certificate prepares you for roles such as Azure AI Solutions Architect, AI Platform Engineer, and Enterprise AI Technical Lead.

Foundational Azure and cloud architecture experience required
Basic ML knowledge expected
No prior AI architect role experience needed

Yes, this is an advanced-level program designed for learners with foundational familiarity with Microsoft Azure and basic machine learning concepts. You should be comfortable navigating the Azure portal before beginning. If you are new to Azure, consider completing a foundational Azure certification or introductory program first.

This program introduces the Microsoft AI and Azure services commonly used to design enterprise AI solutions, including Microsoft Foundry, Azure OpenAI Service, Azure AI Search, Azure AI Language, Azure AI Vision, Azure AI Document Intelligence, Azure AI Speech, Azure AI Content Safety, Azure Policy, Microsoft Purview, Azure API Management, Microsoft Defender for Cloud, Azure DevOps, GitHub Actions, Azure Monitor, and Application Insights. Learning activities emphasize evaluating trade offs, making architectural decisions, and applying best practices through realistic scenarios, with selected opportunities for hands-on platform experience.

You will complete four architecture projects, one per long course, producing deliverables such as architecture diagrams, design specifications, deployment runbooks, governance frameworks, and end-to-end solution documents. These are modeled on real enterprise scenarios and are designed to be portfolio-ready artifacts you can share with employers or discuss in interviews.