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DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure

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Real Exam Format and Information

Exam Name :
DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure 
Exam Duration :
120 Minutes
Number of Questions :
40-60
Exam Fee :
$165 (Varies country to country)
Validity :
2 years
Exam Code :
DP-100
Types Of Questions :
Multiple Choice Questions
Passing Score :
700 out of 1000
Eligibility/Prerequisite :
None
Exam Languages :
English, Japanese, Korean, and Simplified Chinese
Availability : Pearson Vue Test Center / Remote

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DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure

Exam Name : Designing and Implementing a Data Science Solution on Microsoft Azure 

Exam Code : DP-100

Exam Preparation Mode : Classroom / Online

Mock Test : 5-10

Bundle includes : Upto 1000 Questions & Answers

Free Updates : 90 days

Last Update Date : Nov 14, 2024

Offer Price: $136
Price: $165

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DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure Recent Reviews

DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure Training Overview, Salary & Job Profile

DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure is a certification offered by Microsoft that validates the skills and knowledge of individuals in designing and implementing data science solutions using Azure's suite of tools and services. This certification is aimed at data scientists, data engineers, and AI developers who work with data science solutions on the Azure platform.

The DP-100 certification exam covers various topics related to designing and implementing data science solutions, including:

1. Data exploration and preparation: Understanding data sources, performing data cleaning, and transforming data for analysis.

2. Modeling: Building, training, and evaluating machine learning models using Azure Machine Learning services.

3. Feature engineering: Selecting and engineering relevant features for machine learning models.

4. Model deployment and monitoring: Deploying machine learning models into production environments and monitoring model performance.

5. Solution design and architecture: Designing end-to-end data science solutions on Azure, including data ingestion, processing, modeling, and deployment.

6. Experimentation and optimization: Conducting experiments to optimize machine learning models and improve solution performance.

Job benefits of earning the DP-100 certification may include:

1. Career advancement: The DP-100 certification demonstrates expertise in designing and implementing data science solutions on Azure, which can enhance career prospects and open up opportunities for advancement within the field of data science.

2. Increased marketability: Employers often look for candidates with relevant certifications to validate their skills and knowledge. Holding the DP-100 certification can make individuals more marketable to potential employers seeking data science professionals proficient in Azure technologies.

3. Expanded job opportunities: With the increasing adoption of cloud-based technologies for data science and machine learning, individuals with expertise in Azure data services are in high demand. Earning the DP-100 certification can qualify individuals for a wide range of job roles, including data scientist, data engineer, AI developer, and cloud architect.

4. Recognition from Microsoft: Being certified by Microsoft demonstrates a commitment to continuous learning and professional development, which can enhance credibility and recognition within the industry.

5. Access to resources: Microsoft offers a variety of resources, including training materials, documentation, and community forums, to support individuals preparing for the DP-100 certification exam and advancing their careers in data science on Azure.

Overall, earning the DP-100 certification can provide individuals with valuable skills, recognition, and opportunities for career growth in the field of data science on Microsoft Azure.

DP-100: Designing and Implementing a Data Science Solution on Microsoft Azure

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