Perform data science with Azure Databricks
- Offered byMicrosoft
Perform data science with Azure Databricks at Microsoft Overview
Duration | 8 hours |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Perform data science with Azure Databricks at Microsoft Highlights
- Learn how to use modules from the Spark's machine learning library for hyperparameter tuning and model selection
- Understand the three main building blocks in the Spark's machine learning library: transformers, estimators, and pipelines
- Learn how to use Delta Lake to create, append, and upsert data to Apache Spark tables, taking advantage of built-in reliability and optimizations
Perform data science with Azure Databricks at Microsoft Course details
- Describe Azure Data bricks
- Spark architecture fundamentals
- Read and write data in Azure Data bricks
- Work with Data Frames in Azure Data bricks
- Work with user-defined functions
- Discover the capabilities of Azure Data bricks and the Apache Spark notebook for processing huge files
- Understand the Azure Data bricks platform and identify the types of tasks well-suited for Apache Spark
- Learn how to perform data transformations in Data Frames and execute actions to display the transformed data
- Understand the architecture of an Azure Data bricks Spark Cluster and Spark Jobs
Perform data science with Azure Databricks at Microsoft Curriculum
MODULE: 1 Describe Azure Data bricks
Explain Azure Data bricks
Create an Azure Data bricks workspace and cluster
Understand Azure Data bricks Notebooks
Exercise: Work with Notebooks
MODULE: 2 Spark architecture fundamentals
Understand the architecture of Azure Data bricks spark cluster
Understand the architecture of spark job
MODULE: 3 Read and write data in Azure Data bricks
Read data in CSV format
Read data in JSON format
Read data in Parquet format
Read data stored in tables and views
Exercises: Read and write data
MODULE: 4 Work with Data Frames in Azure Data bricks
Describe a Data Frame
Use common Data Frame methods
Use the display function
Exercise: Distinct articles
MODULE: 5 Work with user-defined functions
Write user defined functions
Exercise: Perform Extract, Transform, Load(ETL) operations using user-defined functions
MODULE: 6 Build and query a Delta Lake
Describe the open source Delta Lake
Exercise: Work with basic Delta Lake functionality
Describe how Azure Data bricks manages Delta Lake
Exercise: Use the Delta Lake Time Machine and perform optimization
MODULE: 7 Perform machine learning with Azure Data bricks
Understand machine learning
Exercise: Train a model and create predictions
Understand data using exploratory data analysis
Exercise: Perform exploratory data analysis
Describe machine learning workflows
Exercise: Build and evaluate a baseline machine learning model
MODULE: 8 Train a machine learning model
Perform featurization of the dataset
Exercise: Finish featurization of the dataset
Understand regression modeling
Exercise: Build and interpret a regression model
MODULE: 9 Work with ML flow in Azure Data bricks
Use MLflow to track experiments, log metrics, and compare runs
Exercise: Work with MLflow to track experiment metrics, parameters, artifacts and models
MODULE: 10 Perform model selection with hyperparameter tuning
Describe model selection and hyperparameter tuning
Exercise: Select optimal model by tuning hyperparameters
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