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Machine Learning with Databricks

This course is your gateway to mastering machine learning workflows on Databricks. Dive into data preparation, model development, deployment, and operations, guided by expert instructors. Learn...

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Course Code MLDB
Duration 2 days
Available Formats Classroom, Virtual

This course is your gateway to mastering machine learning workflows on Databricks. Dive into data preparation, model development, deployment, and operations, guided by expert instructors. Learn essential skills for data exploration, model training, and deployment strategies tailored for Databricks. By course end, you'll have the knowledge and confidence to navigate the entire machine learning lifecycle on the Databricks platform, empowering you to build and deploy robust machine learning solutions efficiently.

Skills Gained

After consuming this content, you should be able to:

  • Describe the comprehensive features of the Databricks Data Intelligence Platform tailored for machine learning, including data storage, governance, and exploratory data analysis techniques with Spark and integrated visualization tools.
  • Explain fundamental machine learning concepts, MLflow components for model development, and hyperparameter tuning methods, while performing practical skills in utilizing MLflow for model tracking and tuning, and leveraging Databricks AutoML for rapid model experimentation.
  • Master deployment strategies for batch, pipeline, and real-time scenarios, understanding their advantages and limitations, and demonstrating proficiency in performing batch, pipeline, and real-time inference using Databricks features like DLT and Model Serving.
  • Develop expertise in modern machine learning operations encompassing DevOps, DataOps, and ModelOps principles, and architect machine learning operations solutions based on Databricks-recommended best practices. Perform an end-to-end implementation of a machine learning project using MLOps Stacks and other Databricks capabilities.

Prerequisites

At a minimum, you should be familiar with the following before attempting to take this content:

  • Familiarity with Databricks workspace and notebooks
  • Familiarity with Delta Lake and Lakehouse
  • Intermediate level knowledge of Python
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