Designing and Implementing a Data Science Solution on Azure (beta)
- Product Code: dp-100
- Exam Questions: 613
- Vendor: microsoft
$9.99
$12.99- Updated At: Nov 14, 2024
Designing and Implementing a Data Science Solution on Azure (beta)
This exam is designed for Data Scientists, Engineers, and Architects who want to validate their skills in designing and implementing data science solutions on Azure.
Focus
The Designing and Implementing a Data Science Solution on Azure (beta) certification focuses on Microsoft Azure
Exam Duration
The Designing and Implementing a Data Science Solution on Azure (beta) exam duration is 120 minutes
Num of Question
The exam contains a total of 40 questions
Exam Fee
The exam fee is $165 USD.
Exam Validity
The CCRN-Pediatric certification is valid for 2 years.
Prior Certification
- Exam AZ-403 or other equivalent certifications are recommended but not required.
Exam Format
The Designing and Implementing a Data Science Solution on Azure (beta) exam is a Multiple-choice, case studies, and hands-on exercises.
Passing Conditions
To pass Designing and Implementing a Data Science Solution on Azure (beta) exam, applicants must achieve a minimum score of Passing score of 700 out of 1000
Who Should Take
Data Scientists, Engineers, and Architects planning to design and implement data science solutions on Azure.
- Data Scientist
- Data Engineer
- Data Architect
- Business Intelligence Developer
- Data Analyst
Prerequisites
N/A
Certification Process
- Understand the exam objectives and format.
- Prepare for the exam by studying relevant Azure services, data science concepts, and data engineering best practices.
- Schedule and take the exam.
- Pass the exam to become certified.
Domains with Weights
- domain 01: Data Science with Azure (40%): Design, build, and deploy data science workloads, models, and solutions using Azure services such as Azure Machine Learning, Azure Databricks, and Azure Synapse Analytics.
- domain 02: Data Engineering with Azure (30%): Design, implement, and manage data pipelines, data storage, and data processing using Azure services such as Azure Data Factory, Azure Blob Storage, and Azure Cosmos DB.
- domain 03: Data Governance and Security (15%): Understand and implement data governance and security best practices when using Azure services for data science and data engineering tasks.
- domain 04: Architecture and Design (15%): Understand how to design and implement scalable, secure, and cost-effective data science and data engineering solutions using Azure services.
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