Databricks Certified Associate ML Practitioner for Apache Spark 2.4
The Databricks Certified Associate ML Practitioner for Apache Spark 2.4 certification exam assesses the understanding of and ability to apply machine techniques using the Spark ML library.
The Databricks Certified Associate ML Practitioner for Apache Spark 2.4 certification exam assesses the 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 the understanding of the format and content of the Spark ML library. Candidates will also be assessed in their ability to use Spark ML to accomplish basic tasks in the machine learning workflow.
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
- model and hyperparameter tuning
- model evaluation and selection
- interpreting model results
It is expected that data scientists and data engineers that have been using Spark ML to complete machine learning tasks for six months or more should be able to pass this certification exam.
While it will not be explicitly tested, the candidate must have a working knowledge of Python.
The following Databricks courses should help you prepare for this exam:
- DB 301 - Apache Spark for Machine Learning and Data Science
- Future self-paced data science courses
In addition, Section VI: Advanced Analytics and Machine Learning Overview of Spark: The Definitive Guide should also be helpful in preparation.
The exam details are as follows:
- The exam consists of 60 multiple-choice questions. Candidates will have 120 minutes to complete the exam.
- The minimum passing score for the exam is 70 percent. This translates to correctly answering a minimum of 42 of the 60 questions.
- The exam will be conducted via an online proctor.
- During the exam, candidates will be provided with a PDF version of the Apache Spark documentation for Python and a digital notepad for taking notes and writing example code.
Other exam details are available via the Certification FAQ.
Please find tech requirements and preparation instructions on Kryterion’s Online Proctored Exam Support page.
To register for this certification please click the button below and follow the instructions to create a certification account and process payment.