Machine learning with Azure Databricks (DP-3014)

Course Outline

Embark on an enriching journey with this hands-on instructor-led Microsoft course, 'Machine Learning with Azure Databricks (DP-3014),' designed to empower you with cloud-scale capabilities for data analytics and machine learning. Within this immersive one-day experience, you'll delve into Azure Databricks, a versatile platform enabling data scientists and machine learning engineers to implement robust solutions at scale, revolutionizing the way data insights are extracted and utilized.

Machine learning with Azure Databricks (DP-3014) Benefits

In this course, you will learn how to:
- Gain proficiency in utilizing Azure Databricks, a cloud service offering a scalable platform for data analytics using Apache Spark.
- Acquire practical knowledge and hands-on experience in employing Spark to transform, analyze, and visualize data at scale.
- Develop skills in training machine learning models and evaluating their performance within the Azure Databricks environment.
- Learn to leverage MLflow, an open-source platform for managing the machine learning lifecycle, seamlessly integrated with Azure Databricks.
- Master the art of hyperparameter tuning and optimization using Hyperopt library, enhancing the efficiency of machine learning workflows.
- Explore the simplicity and effectiveness of AutoML in Azure Databricks for automating the model building process.
- Dive into the realm of deep learning, understanding concepts and training models for complex AI workloads like forecasting, computer vision, and natural language processing.
Training Prerequisites

To fully benefit from this course, please ensure you possess proficiency in Python for data exploration and machine learning model training using popular open-source frameworks such as Scikit-Learn, PyTorch, and TensorFlow.

Machine learning with Azure Databricks Training Outline

Explore Azure Databricks

Get started with Azure Databricks
Identify Azure Databricks workloads
Understand key concepts
Exercise Explore Azure Databricks
Knowledge check

Use Apache Spark in Azure Databricks

Get to know Spark
Create a Spark cluster
Use Spark in notebooks
Use Spark to work with data files
Visualize data
Exercise Use Spark in Azure Databricks
Knowledge check

Train a machine learning model in Azure Databricks

Understand principles of machine learning
Machine learning in Azure Databricks
Prepare data for machine learning
Train a machine learning model
Evaluate a machine learning model
Exercise Train a machine learning model in Azure Databricks
Knowledge check

Use MLflow in Azure Databricks

Capabilities of MLflow
Run experiments with MLflow
Register and serve models with MLflow
Exercise Use MLflow in Azure Databricks
Knowledge check

Tune hyperparameters in Azure Databricks

Optimize hyperparameters with Hyperopt
Review Hyperopt trials
Scale Hyperopt trials
Exercise Optimize hyperparameters for machine learning in Azure Databricks
Knowledge check

Use AutoML in Azure Databricks

What is AutoML?
Use AutoML in the Azure Databricks user interface
Use code to run an AutoML experiment
Exercise Use AutoML in Azure Databricks
Knowledge check

Train deep learning models in Azure Databricks

Understand deep learning concepts
Train models with PyTorch
Distribute PyTorch training with Horovod
Exercise Train deep learning models on Azure Databricks
Knowledge check