Databricks Certified Professional Data Scientist


  • Product Code: databricks-certified-professional-data-scientist
  • Exam Questions: 119
  • Vendor: databricks

$9.99

$12.99
  • Updated At: Nov 14, 2024
Databricks Certified Professional Data Scientist

Demonstrate ability to design, implement, and deploy scalable data science solutions using Apache Spark on Databricks.

Focus

The Databricks Certified Professional Data Scientist certification focuses on Data Science and Machine Learning

Exam Duration

The Databricks Certified Professional Data Scientist exam duration is 120 minutes

Num of Question

The exam contains a total of 65 questions

Exam Fee

The exam fee is 150 USD.

Exam Validity

The CCRN-Pediatric certification is valid for 2 years.

Prior Certification
  • Databricks Certified Associate Data Engineer
Exam Format

The Databricks Certified Professional Data Scientist exam is a Multi-choice questions and hands-on projects

Passing Conditions

To pass Databricks Certified Professional Data Scientist exam, applicants must achieve a minimum score of 70% score

Who Should Take

Professionals who want to demonstrate their ability to design, implement, and deploy scalable data science solutions using Apache Spark on Databricks.

  • Data Scientist
  • Machine Learning Engineer
  • Data Engineer
Prerequisites

1 year of experience in data science and machine learning

Or can substitute with certifications:

  • Databricks Certified Associate Data Engineer
  • Certified Data Scientist (CDISC)
Certification Process
  • Step 1: Prepare for the Exam
  • Step 2: Register and Schedule the Exam
  • Step 3: Pass the Exam
  • Step 4: Get Certified
Domains with Weights
  • Domain 1: Data Engineering (30%): Design, implement, and deploy scalable data engineering solutions using Apache Spark on Databricks.
  • Domain 2: Data Science and Machine Learning (60%): Design, implement, and deploy scalable data science and machine learning solutions using Apache Spark on Databricks.
  • Domain 3: Databricks Platform (10%): Implement and deploy data science and machine learning workloads on the Databricks platform.

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