CERTALYTH Certified Generative AI & Agent Developer

CCGAAD · CT-AIA-A · Generative AI and AI Agents on Microsoft Azure

Create generative AI apps and agents on Azure AI.

Microsoft Certified: Azure AI Apps and Agents Developer Associate (AI-103)

40 hoursCertificate with unique codeMultiple-choice exam

149EUR

Full bundle: course PDF + online exam + certification.

Recertification every 3 years: 99 EUR

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About the course

Discover how to develop intelligent applications and AI agents using Azure AI services, generative models, and orchestration techniques. Aligned with the Microsoft AI-103 exam.

Focus: Applications with generative models, AI agents, and orchestration on Azure AI.

What you'll learn

Integrate generative models into applications

Build orchestrated AI agents

Apply responsible AI best practices

Deploy scalable AI solutions on Azure

Sample questions (free)

A sample from the official exam set — correct answers are revealed only during the actual exam.

CERTALYTH Certified Generative AI & Agent Developer

About the course

What you'll learn

Sample questions (free)

You are designing a production system that calls an Azure-hosted LLM. To reduce the risk of credential leakage and to enable automated rotation, which authentication approach is most appropriate for server-side application code running in Azure?

An enterprise needs low-latency responses for users across Europe and resilient service during regional outages. Which deployment pattern best balances latency and availability for an Azure AI endpoint?

You need to restrict who can (1) deploy and update model endpoints and (2) only call inference APIs. Which access control approach aligns best with least privilege and separation of duties?

After deploying a text-generation service you observe sporadic cost spikes caused by unusually long responses and retries. Which combination of operational controls will most directly reduce cost volatility while preserving availability?

Your security team requires that AI endpoints are accessible only from a corporate VNet. Which operational implication must you plan for when enabling a private endpoint for an Azure AI service?