Create and manage assets and resources in the Azure Machine Learning workspace, using the portal, the studio, the Azure CLI, and especially the Python SDK (v2).
Build and run pipelines with the no-code designer in the Azure Machine Learning studio.
Use Automated Machine Learning to explore featurization and algorithms.
Train and track machine learning models in Azure Machine Learning notebooks using MLflow.
Train and track machine learning models using scripts as Azure Machine Learning jobs, using MLflow.
Create, run, and schedule Azure Machine Learning pipelines.
Deploy models to real-time and batch endpoints.
Apply Responsible AI principles to data, models, and model training.
Design a MLOps solution and design for monitoring and retraining.
