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
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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.
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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
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