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Machine learning with Azure Databricks (DP-3014)
Course 8686
1 DAY COURSE

Price:
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

Learning Objectives

  1. Explore Azure Databricks
  • Introduction to Azure Databricks as a cloud service providing a scalable platform for data analytics.
  • Use of Apache Spark in Azure Databricks for performing data transformations, analysis, and visualizations at scale.
  1. Train a Machine Learning Model in Azure Databricks
  • Understanding how data is used for training predictive models in Azure Databricks.
  • Overview of the commonly used machine learning frameworks supported by Azure Databricks.
  1. Use MLflow in Azure Databricks
  • Introduction to MLflow as an open-source platform managing the machine learning lifecycle.
  • Insight into how MLflow is natively supported in Azure Databricks.
  1. Tune Hyperparameters in Azure Databricks
  • The important role of tuning hyperparameters in machine learning.
  • Using the Hyperopt library in Azure Databricks for automated hyperparameters optimization.
  1. Use AutoML in Azure Databricks
  • An overview of AutoML’s role in simplifying the process of building effective machine learning models.
  • Insight into how AutoML fits into the Azure Databricks ecosystem.
  1. Train Deep Learning Models in Azure Databricks
  • Understanding deep learning and its use of neural networks for training machine learning models.
  • Looking at the complex forecasting, computer vision, natural language processing, and other AI workloads handled by deep learning in Azure Databricks.
Course Dates
Attendance Method

How will you be attending the class?

Selecting 'Live Virtual' allows you to attend remotely from work or home. You will receive email communication well before the class starts with detailed instructions on how to validate your equipment and connect to the classroom for a quality learning experience.

Additional Details (optional)

Private Team Training

Interested in this course for your team? Please complete and submit the form below and we will contact you to discuss your needs and budget.