Duration
4 days.
Prerequisites
Before attending this course, students must have:
- Azure Fundamentals
- Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
- How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn.
Who Can Benefit?
This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.
Outline for Designing and Implementing a Data Science Solution on Azure Training
Outline
- Design a data ingestion strategy for machine learning projects
- Design a machine learning model training solution
- Design a model deployment solution
- Explore Azure Machine Learning workspace resources and assets
- Explore developer tools 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
01/16/2024 - 01/19/2024
09:00 AM - 05:00 PM
Eastern Standard Time
USD $2,380.00
03/11/2024 - 03/14/2024
09:00 AM - 05:00 PM
Eastern Standard Time
USD $2,380.00
06/03/2024 - 06/06/2024
09:00 AM - 05:00 PM
Eastern Standard Time
USD $2,380.00