AI-300: Operationalizing Machine Learning and Generative AI Solutions

As a candidate for this Microsoft Certification, you should have subject matter expertise in setting up infrastructure for machine learning operations (MLOps) and generative AI operations (GenAIOps) solutions on Azure, together referred to as AI operations (AIOps). You need experience training, optimizing, deploying, and maintaining traditional machine learning models by using Azure Machine Learning, in addition to experience deploying, evaluating, monitoring, and optimizing generative AI applications and agents by using Microsoft Foundry.

You should have a data science background with experience in Python programming and an entry-level understanding of DevOps practices, including using tools like GitHub Actions and working with command-line interfaces (CLIs).

Additionally, you need knowledge and experience in MLOps by using:

• Machine Learning.

• Foundry.

• GitHub Actions.

• Infrastructure as code (IaC) practices with Bicep and Azure CLI.

Your responsibilities for this role include:

• Designing and implementing MLOps infrastructure.

• Implementing machine learning model lifecycle and operations.

• Designing and implementing GenAIOps infrastructure.

• Implementing generative AI quality assurance and observability.

• Optimizing generative AI systems and model performance.

You work with data scientists, DevOps teams, and stakeholders to deliver scalable AI solutions with comprehensive automation and monitoring.