Azure MLOps is a course designed to help students and professionals understand how to use Azure Machine Learning (AML) for end-to-end machine learning operations. In the course, students learn the fundamentals of AML, how to deploy and manage ML models in the cloud, utilize Azure hardware and software resources for ML, and use the MLOps framework to monitor and manage ML models. Through real-world scenarios and hands-on labs, students gain the knowledge and skills needed to build and deploy ML models in production. They will learn best practices for architecture, deployment, and operationalizing these models. The course also covers the security and compliance aspects of running ML models in the cloud. This knowledge is helpful in the AI and ML job market.
Flexible Dates
Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.4-Hour Sessions
Training never been so convenient- attend training sessions 4-hour long for easy learning.Destination Training
Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.Live Online Training (Duration : 16 Hours) | |||
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There are no prerequisites for learning Azure MLOps. However, it would be beneficial if you have knowledge of machine learning applications and basic programming skills. Additionally, having some experience with Azure cloud services could prove helpful when taking a course or course related to Azure MLOps.
Azure MLOps training is an ideal choice for data scientists and other IT professionals looking to get acquainted with, and leverage the benefits provided by, the Microsoft Azure cloud platform. This training is also beneficial to developers and technology professionals looking to deploy, manage and maintain machine learning models and applications on the cloud. Data analytics professionals and DevOps professionals using Azure can also learn how to integrate their existing CI/CD pipelines with Azure MLOps to automate and monitor their ML model deployments and updates. In addition, IT administrators, C-level executives and business stakeholders who are responsible for the performance and scalability of their organization’s Azure MLOps platform can also benefit from this training and gain the tools needed to improve the productivity and reliability of their AI and ML initiatives.
1. Learn the basics of Azure MLOps and Machine Learning (ML) technologies.
2. Understand the key concepts of CI/CD Automation with Azure DevOps and Azure ML services.
3. Design and deploy workflow pipelines to automate the ML model training.
4. Configure and manage ML models, experiments, and compute targets in Azure ML.
5. Integrate Azure ML and DevOps services with external systems and software.
6. Implement ML feature engineering and model management in pipelines.
7. Train and serve predictive models using Azure ML services.
8. Perform hyperparameter optimization for model tuning and improvement.
9. Monitor and manage MLOps models and metrics in Azure Azure Dashboard.
10. Create model accuracy reports with Azure ML Explainer.