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Microsoft 070-774 certification exam is offered to individuals who want to demonstrate their proficiency in performing cloud data science with the Azure Machine Learning suite. 70-774 exam covers a wide range of topics that include data preparation, modeling, deployment, and monitoring using Microsoft Azure. It also evaluates the candidate's ability to implement machine learning algorithms, interpret results, and generate insights.
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One of the key topics covered in the 070-774 certification exam is predictive modeling. This includes understanding how to use Azure Machine Learning to build, train, and deploy machine learning models using a variety of algorithms and techniques. Candidates must also be able to evaluate and optimize their models to ensure they are performing at their best.
Reference: https://www.microsoft.com/en-us/learning/exam-70-774.aspx
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Microsoft 070-774 is a certification exam designed by Microsoft to test a candidate's proficiency in performing cloud-based data science tasks using Azure Machine Learning. 70-774 exam is designed to verify a candidate's ability to carry out various tasks related to developing and deploying data models, preparing data for processing, and building machine learning solutions.
Microsoft 070-774 certification exam is a valuable credential for data scientists looking to advance their careers in cloud data science and machine learning. Candidates who wish to take the exam should have a solid understanding of the Azure environment, machine learning algorithms, and programming languages such as Python and R. Obtaining this certification can lead to better job prospects, higher salaries, and increased recognition in the industry.
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Microsoft 70-774 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Operationalize and Manage Azure Machine Learning Services | - Deploy models using Azure ML - Consume ML models - Consume related Cognitive Services APIs - Manage ML projects and workspaces |
| Develop Machine Learning Models | - Validate models - Initialize and train models - Select appropriate algorithm/method |
| Use Other Services for Machine Learning | - Perform data sciences at scale via HDInsight - Build/use neural networks (Microsoft Cognitive Toolkit) - Perform database analytics using SQL Server R Services - Streamline development with existing resources |
| Prepare Data for Analysis in Azure Machine Learning | - Cleanse data for Azure ML - Explore and summarize data - Import and export data to/from Azure ML - Perform feature engineering |
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