The Azure MLOps course is designed for data scientists, ML engineers, and DevOps professionals who want to streamline the lifecycle of machine learning models using Azure Machine Learning (Azure ML), Azure DevOps, and CI/CD pipelines. This course provides hands-on experience in automating, deploying, monitoring, and managing ML models in a production environment using MLOps best practices.

Who Should Enroll Now:

• Machine Learning Engineers looking to optimize and automate ML workflows.
• Data Scientists who want to deploy models efficiently in production.
• DevOps Engineers integrating AI into CI/CD pipelines.
• AI and Cloud Professionals working with Azure Machine Learning.

Key Learning Objectives:

• Implement MLOps best practices in Azure.
• Automate model training, testing, and deployment using Azure ML Pipelines.
• Use Azure DevOps for CI/CD automation of ML models.
• Monitor model performance with Azure Application Insights and Model Drift Detection.
• Deploy and manage machine learning models at scale in Azure Kubernetes Service (AKS).

Why Choose This Course?
✅ Industry-relevant hands-on training with real-world MLOps scenarios.
✅ Learn end-to-end machine learning lifecycle automation.
✅ Covers Azure DevOps, ML pipelines, CI/CD integration, and model monitoring.
✅ Gain practical knowledge for enterprise AI and MLOps roles.