Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this one-day course, you’ll learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.
- Presencial
- Training
DP-090: Implementing a Machine Learning Solution with Microsoft Azure Databricks
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- Horário
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Laboral
das 9h00 às 17h00
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- Local
- Live Training
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- Calendário
- 19 Dez. 2022 a 19 Dez. 2022
Cursos relacionados
Destinatários
This course is designed for data scientists with experience of Pythion who need to learn how to apply their data science and machine learning skills on Azure Databricks
Pré-requisitos
- Before attending this course, you should have experience of using Python to work with data, and some knowledge of machine learning concepts.
Objetivos
- Provision an Azure Databricks workspace and cluster
- Use Azure Databricks to train a machine learning model
- Use MLflow to track experiments and manage machine learning models
- Integrate Azure Databricks with Azure Machine Learning
Programa
- Get started with Azure Databricks
- Work with data in Azure Databricks
- Prepare data for machine learning with Azure Databricks
- Train a machine learning model with Azure Databricks
- Use MLflow to track experiments in Azure Databricks
- Manage machine learning models in Azure Databricks
- Track Azure Databricks experiments in Azure Machine Learning
- Deploy Azure Databricks models in Azure Machine Learning
Get started with Azure Databricks
- Understand Azure Databricks
- Provision Azure Databricks workspaces and clusters
- Work with notebooks in Azure Databricks
- Exercise – Get started with Azure Databricks
- Knowledge check
Work with data in Azure Databricks
- Understand dataframes
- Query dataframes
- Visualize data
- Exercise – Work with data in Azure Databricks
- Knowledge check
Prepare data for machine learning with Azure Databricks
- Understand machine learning concepts
- Perform data cleaning
- Perform feature engineering
- Perform data scaling
- Perform data encoding
- Exercise – Prepare data for machine learning
- Knowledge check
Train a machine learning model with Azure Databricks
- Understand Spark ML
- Train and validate a model
- Use other machine learning frameworks
- Exercise – Train a machine learning model
- Knowledge check
Use MLflow to track experiments in Azure Databricks
- Understand capabilities of MLflow
- Use MLflow terminology
- Run experiments
- Exercise – Use MLflow to track an experiment
- Knowledge check
Manage machine learning models in Azure Databricks
- Describe considerations for model management
- Register models
- Manage model versioning
- Exercise – Manage models in Azure Databricks
- Knowledge check
Track Azure Databricks experiments in Azure Machine Learning
- Describe Azure Machine Learning
- Run Azure Databricks experiments in Azure Machine Learning
- Log metrics in Azure Machine Learning with MLflow
- Run Azure Machine Learning pipelines on Azure Databricks compute
- Exercise – Use Azure Databricks with Azure Machine Learning
- Knowledge check
Deploy Azure Databricks models in Azure Machine Learning
- Describe considerations for model deployment
- Plan for Azure Machine Learning deployment endpoints
- Deploy a model to Azure Machine Learning
- Troubleshoot model deployment
- Exercise – Deploy an Azure Databricks model in Azure Machine Learning
- Knowledge check
Ao concluir com aproveitamento esta formação, cumprindo a percentagem mínima de 70% de assiduidade e após avaliação ao curso, o formando poderá receber o seu Certificado Microsoft de conclusão e o badge digital para partilhar com a sua rede profissional online.
