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EbookBell Team
4.7
26 reviewsDesigning and creating a suitable working environment for data science workloads.
Exploring data.Training machine learning models. Implementing pipelines. Running jobs to prepare for production.
Managing, deploying, and monitoring scalable machine learning solutions.
As a candidate for this exam, you should have knowledge and experience in data science by using
Azure Machine Learning
MLflow
Design and prepare a machine learning solution (20-25%)
Explore data and train models (35-40%)
Prepare a model for deployment (20-25%)
Deploy and retrain a model (10-15%)
