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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.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
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The certification obtained from passing DP-100 exam is proof of intermediate skills in data science since it is within the associate hierarchy. Apart from applying for and getting a job in a preferred company, you can also expand your skills in an area of interest. With the role-based scheme, there are expert certifications awaiting you to earn. They include the Microsoft Certified: Azure Solutions Architect Expert and the Microsoft Certified: Azure DevOps Engineer Expert.
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These are following steps for registering the DP-100 exam. Step 1: Visit to Microsoft Exam Registration Step 2: Signup/Login to MICROSOFT account Step 3: Search for MICROSOFT DP-100 Certifications Exam Step 4: Select Date and Center of examination and confirm with payment value of $165
| Section | Objectives |
|---|---|
| Topic 1: Train machine learning models | - Train models using Azure Machine Learning - Tune hyperparameters and evaluate models |
| Topic 2: Explore and analyze data | - Perform exploratory data analysis - Ingest and prepare data for modeling |
| Topic 3: Deploy and consume models | - Monitor deployed models and endpoints - Deploy models to endpoints |
| Topic 4: Optimize and manage models | - Improve model performance - Track experiments and manage model lifecycle |
| Topic 5: 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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