Implementing Machine Learning with Azure Databricks (DP-3014)
Description
In this course, you'll learn how to use Azure Databricks to train and deploy machine learning models.
Azure Databricks is a fully managed, cloud-based data analytics platform, which empowers developers to accelerate AI and innovation by simplifying the process of building enterprise-grade data applications. Built as a joint effort by Microsoft and the team that started Apache Spark, Azure Databricks provides data science, engineering, and analytical teams with a single platform for big data processing and machine learning.
You are an aspiring Data Scientist or AI Engineer who needs to train and manage Machine Learning models by using Azure Databricks.
After completing this course, you will be able to:
- Train machine learning models using Azure Databricks
- Use MLflow to track machine learning experiment runs in Azure Databricks
- Tune hyperparameters for machine learning models in Azure Databricks
- Use Auto ML to train models in Azure Databricks
- Train deep learning models in Azure Databricks
Prerequisites
Before attending this course, you should have:
- Experience of programming with Python
- Experience of working with Microsoft Azure services
Course outline
- Explore Azure Databricks
- Train a machine learning model in Azure Databricks
- Use MLflow in Azure Databricks
- Tune hyperparameters in Azure Databricks
- Use AutoML in Azure Databricks
- Train deep learning models in Azure Databricks
Course material
In the course "Implementing a Machine Learning solution with Azure Databricks" (DP-3014) we use Microsoft Official Courseware. We will ensure that you receive this (digital) material at the start of the course.
Available dates
| Title | Date |
|---|---|
| DP3014 |
| Title | Date |
|---|---|
| DP3014 |
