This course uses a case study driven approach to explore the fundamentals of Spark Programming with Databricks, including Spark architecture, the DataFrame API, Structured Streaming, and query optimization.

In this course data analysts and data scientists practice the full data science workflow by exploring data, creating features and building models, performing hyperparameter tuning, and tracking parameters and managing models with MLflow. By the end of this course, you will have built end-to-end machine learning models ready for production. 

In this 1-day course, data scientists and data engineers learn best practices for managing experiments, projects, and models using MLflow. Students build a pipeline to log and deploy machine learning models, as well as explore common production issues faced when deploying machine learning solutions and monitoring these models once they have been deployed into production.

This 1-day course aims to help participants with or without a programming background develop just enough experience with Scala to begin using the Apache Spark programming APIs.

This 1-day course aims to help participants with or without a programming background develop just enough experience with Python to begin using the Apache Spark programming APIs.

This 1-day course provides a brief introduction to the Apache Spark architecture, the DataFrames API, and one choice from several electives, covering the fundamentals of the Apache Spark framework.

This 3-day course provides a thorough review of the Apache Spark framework, including the "Spark fundamentals" with specific emphasis on skills development and the unique needs of a Data Engineering team through the use of lecture and hands-on labs.

This course offers a deep dive into the processes of tuning Spark applications, developing best practices and avoiding many of the common pitfalls associated with developing Spark applications.

Directed at those who want to use Delta Lake for ETL processing on data lakes. The course ends with a capstone project building a complete data pipeline using Delta Lake

This course is to be replaced by Scalable Machine Learning with Apache Spark  

This 3-day course provides an introduction to the "Spark fundamentals," the "ML fundamentals," and a cursory look at various Machine Learning and Data Science topics with specific emphasis on skills development and the unique needs of a Data Science team through the use of lecture and hands-on labs.

This course covers the fundamentals of neural networks with TensorFlow and how to scale your deep learning models with Spark.

In this course, students learn about Reinforcement Learning (RL) paradigm and get hands-on experience on developing/coding RL algorithms.

This capstone is a guided project focused on establishing a data pipeline to transform data from source through the bronze, silver, and gold layers for a manufacturing organization

This capstone is a guided project focused on establishing a data pipeline to transform data from source through the bronze, silver, and gold layers for a retail organization

This capstone is a guided project focused on establishing a data pipeline to transform data from source through the bronze, silver, and gold layers for a healthcare organization

This capstone is a guided project focused on establishing a data pipeline to transform data from source through the bronze, silver, and gold layers for a finance organization

This course offers a thorough, hands-on overview of how to scale R applications with Apache Spark