This course runs for a duration of 4 Days.
The class will run daily from 8:00 AM CT to 4:00 PM CT.
Class Location: Virtual LIVE Instructor Led - Virtual Live Classroom.
The Azure Data Scientist applies their knowledge of data science and machine learning to implementing and running machine learning workloads on Microsoft Azure; in particular, using Azure Machine Learning Service. This entails planning and creating a suitable working environment for data science workloads on Azure, running data experiments and training predictive models, managing and optimizing models, and deploying machine learning models into production.
Course Objectives
Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.
Who Should Attend?
This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.
Design a data ingestion strategy for machine learning projects
Design a machine learning model training solution
Design a model deployment sulution
Explore Azure Machine Learning workspace resources and assets
Explore developer touls for workspace interaction
Make data available in Azure Machine Learning
Work with compute targets in Azure Machine Learning
Work with environments in Azure Machine Learning
Find the best classification model with Automated Machine Learning​
Track model training in Jupyter notebooks with MLflow
Run a training script as a command job in Azure Machine Learning
Track model training with MLflow in jobs
Run pipelines in Azure Machine Learning
Perform hyperparameter tuning with Azure Machine Learning
Deploy a model to a managed online endpoint
Deploy a model to a batch endpoint