Who is this training for?
- Intermediate
- Data Scientist
Training objectives
You'll be able to implement machine learning solutions at scale using Azure Databricks and Apache Spark.
Summary
Azure Databricks is a cloud-scale platform for data analytics and machine learning. Data scientists and machine learning engineers can use Azure Databricks to implement machine learning solutions at scale.
Course outline
- Explore Azure Databricks
- Use Apache Spark in 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
Approach and methodology
Practical and structured approach combining focused theory and guided workshops. Participants gradually implement a machine learning solution with Azure Databricks through real-world exercises inspired by business scenarios, promoting immediate application of learning. They learn how to prepare data, train and evaluate models, and deploy and monitor machine learning solutions at scale in a Databricks environment. Led by a Microsoft certified trainer, the training focuses on interactivity and the development of directly transferable technical skills to industrialize Machine Learning projects in a professional context.
Prerequisites
- Experience using Python to explore data
- Have trained machine learning models with common open source frameworks, such as Scikit-Learn, PyTorch, and TensorFlow
Recommendations
Consider taking the Build Machine Learning Models learning path before you start this one.
