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Career Opportunities, Roles, and Salary

After obtaining the Microsoft Certified: Azure Data Scientist Associate certification, you become eligible for the data scientist role. Also, with this certification, you can expect to earn a decent remuneration of about $97k on average annually, as stated by PayScale.com. The expected career paths for a data scientist also include senior data scientist with a salary potential of $126,778 and data science manager with a salary potential of $136,781. Another possible path is that of a data science director with a potential pay of $157,095 annually. However, remember that besides, such a certificate work experience also matters.

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Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam

Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam which is related to Microsoft Certified Azure Data Scientist Associate Certification. This DP-100 exam validates the ability to apply scientific rigor and data exploration techniques to gain actionable insights and communicate results to stakeholders. This DP-100 exam also tests the Candidate knowledge to use machine learning techniques to train, evaluate, and deploy models to build AI solutions that satisfy business objectives. Candidates must have skills to use applications that involve natural language processing, speech, computer vision, and predictive analytics. Azure Data Scientist usually hold or pursue this certification and you can expect the same job role after completion of this certification.

Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx

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Microsoft DP-100 Korean Exam Syllabus Topics:

SectionObjectives
Explore and analyze data- Ingest and prepare data for modeling
- Perform exploratory data analysis
Train machine learning models- Tune hyperparameters and evaluate models
- Train models using Azure Machine Learning
Optimize and manage models- Track experiments and manage model lifecycle
- Improve model performance
Deploy and consume models- Monitor deployed models and endpoints
- Deploy models to endpoints
Design and prepare a machine learning solution- Plan and configure Azure Machine Learning workspace
- Select appropriate Azure services for machine learning workloads
- Manage compute and data assets

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