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Databricks Exam Syllabus

Machine Learning Associate syllabus, skills measured, and exam topics

Become a Databricks Certified Machine Learning Associate and enhance your skills in machine learning with Databricks tools and best practices.

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Exam details

Quick facts pulled from the official source for faster scanning.

Total number of scored questions 48
Question types Multiple choice
Languages English, 日本語 , Português BR , 한국어
Delivery Method Online or test center
Prerequisites None, but related training highly recommended
Recommended experience 6+ months of hands-on experience performing the machine learning tasks outlined in the exam guide
Recertification Recertification is required every two years to maintain your certified status. To recertify, you must take the current version of the exam. Please review the “Getting Ready for the Exam” section below to prepare for your recertification exam.
Unscored content Exams may include unscored items to gather statistical information for future use. These items are not identified on the form and do not impact your score. Additional time is factored into the exam to account for this content.

What to know before you study

These sections explain the role, audience, and exam framing behind the outline.

Databricks Certified Machine Learning Associate

  • The Databricks Certified Machine Learning Associate certification exam assesses an individual’s ability to use Databricks to perform basic machine learning tasks. This includes an ability to understand and use Databricks and its machine learning capabilities like AutoML, Unity Catalog and select features of MLflow. It also assesses the ability to explore data and perform feature engineering. Additionally, the exam assesses model building through training, tuning and evaluation and selection. Finally, an ability to deploy machine learning models is assessed. Individuals who pass this certification exam can be expected to complete basic machine learning tasks using Databricks and its associated tools.
  • Databricks Machine Learning – 38%
  • ML Workflows – 19%
  • Model Development – 31%
  • Model Deployment – 12%

Getting Ready for the Exam

  • Review the Machine Learning Associate Exam Guide to understand what will be on the exam
  • Take the related training outlined in the Exam Guide
  • Register for the exam
  • Review the technical requirements for taking an online proctored exam and run a system check
  • Review the exam guide again to identify any gaps
  • Study to fill in the gaps
  • Take your exam!
  • All machine learning code within this exam will be in Python. In the case of workflows or code not specific to machine learning tasks, data manipulation code could be provided in SQL.

Registration

  • To register for a certification exam, please log in or create an account on our exam delivery platform .