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AI-300: Machine Learning Operations Engineer Associate Certification
Machine learning operations (MLOps) and generative AI operations (GenAIOps) combine data science, DevOps, and cloud engineering to deploy, monitor, and maintain AI solutions in production. This path prepares you for the AI-300 exam and the Microsoft Certified: Machine Learning Operations Engineer Associate certification. You'll learn to build MLOps and GenAIOps infrastructure on Azure, manage the model lifecycle, evaluate generative AI quality and observability, and optimize AI system performance.
- AI-300: Designing and Implementing an MLOps Infrastructure (video course) - AI-300: Implementing Machine Learning Model Lifecycle and Operations (video course) - AI-300: Designing and Implementing a GenAIOps Infrastructure (video course) - AI-300: Implementing Generative AI Quality Assurance and Observability (video course) - AI-300: Optimizing Generative AI Systems and Model Performance (video course)
Content in this path
AI-300: Machine Learning Operations Engineer Associate Certification
Watch the following courses to get learning about MLOps and GenAIOps on Azure and prepare for the AI-300 exam!
Try this certification path for free
Build confidence to ace your certification exam with a variety of prep tools, including video courses, labs, and practice exams.
What You'll Learn
- How to design and implement an MLOps infrastructure
- How to implement the machine learning model lifecycle and operations
- How to design and implement a GenAIOps infrastructure
- How to implement generative AI quality assurance and observability
- How to optimize generative AI systems and model performance
- How to operationalize machine learning and generative AI solutions to prepare for the AI-300 exam
- Learners should have a data science background with Python programming experience and an entry-level understanding of DevOps practices, such as using GitHub Actions and working with command-line interfaces (CLIs).
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