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Databricks Certified Machine Learning Associate

Use Databricks to perform basic machine learning tasks

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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 Machine Learning and its capabilities like AutoML, Feature Store, and select capabilities of MLflow. It also assesses the ability to make correct decisions in machine learning workflows and implement those workflows using Spark ML. Finally, an ability to understand advanced characteristics of scaling 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.

This exam covers:

  1. Databricks Machine Learning – 29%
  2. ML Workflows – 29%
  3. Spark ML – 33%
  4. Scaling ML Models – 9%

Assessment Details

Type: Proctored certification

Total number of questions: 45

Time limit: 90 minutes

Registration fee: $200

Question types: Multiple choice

Test aides: None allowed

Languages: English

Delivery method: Online proctored

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   

Validity period: 2 years

Recertification: Recertification is required to maintain your certification status. Databricks Certifications are valid for two years from issue date.

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.

Related Training

Getting Ready for the Exam

  1. Review the Machine Learning Associate Exam Guide to understand what will be on the exam
  2. Take the related training
  3. Register for the exam
  4. Review the technical requirements and run a system check
  5. Review the exam guide again to identify any gaps
  6. Study to fill in the gaps
  7. 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

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