Develop dynamic reports with Microsoft Power BI

Transform and load data, define semantic model relationships and calculations, create interactive visuals, and distribute reports using Power BI.

Validate your technical skills and open doors to new possibilities of advancement with Microsoft Applied Skills.

To train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow, you can decide to deploy your model to an online endpoint for real-time predictions. Throughout this learning path, you explore how to set up your Azure Machine Learning workspace, after which you train and deploy a machine learning model.

Validate your technical skills and open doors to new possibilities of advancement with Microsoft Applied Skills.

This learning path helps you prepare for the Implement security through a pipeline assessment using Azure DevOps. Learn how to configure and secure Azure Pipelines. You’ll also get opportunities to practice hands-on skills. These skills include configuring secure access to pipeline resources, configuring, and validating permissions, configuring a project and repository structure, extending a pipeline, configuring pipelines to use variables and parameters securely, and managing identity for projects, pipelines, and agents.

The opportunity is yours to lead the era of AI with Microsoft. Power your organization’s AI transformation with Microsoft Cloud. The AI you can trust.

Validate your technical skills and open doors to new possibilities of advancement with Microsoft Applied Skills.

In this learning path, you practice implementing Azure Monitor to collect, analyze and act on monitoring telemetry from Azure environments. You learn to configure and interpret monitoring for virtual machines, networking, and web applications.