Databricks Certified Associate Spark ML Practitioner for Apache Spark 2.4

Summary

Coming soon!

Note: Due to technical issues, we have had to temporarily suspend our exams. We expect to be back up and running by early April.

The Databricks Certified Associate Spark ML Practitioner for Apache Spark 2.4 certification exam assesses the understanding of and ability to apply machine learning techniques using Spark ML.

Description

Candidates will be assessed in their understanding of basic machine learning concepts and machine learning workflow knowledge, including supervised learning vs. unsupervised learning, regression vs. classification, clustering, cross validation, model tuning, model evaluation, and model interpretation, as well as their understanding of the format and content of the Spark ML library. Candidates will be also be assessed in their ability to use Spark ML to accomplish basic tasks in the machine learning workflow.

Prerequisites

The minimally qualified candidate should:

  • be able to apply the Spark ML library to complete individual tasks in the machine learning workflow
  • understand the structure and format of the Spark ML library
  • have a basic knowledge of general machine learning and workflow, including supervised vs. unsupervised learning, regression vs. classification, clustering, cross validation, model tuning, model evaluation, and model interpretation

It's expected that machine learning practitioners using Spark ML to complete machine learning tasks for one year or more should be able to pass this certification exam.

The following Databricks courses will help you prepare for this exam: