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To pass the 070-774 exam, you must have a deep understanding of statistics, machine learning algorithms, and data analysis tools. 070-774 exam will test your ability to create and manage machine learning models using Azure Machine Learning. You will also need to demonstrate your expertise in designing experiments, creating data visualizations, and using Jupyter notebooks to manipulate and analyze data.
Microsoft 070-774 exam is a must-take for those who aim to be proficient in creating and implementing machine learning models, deploying and maintaining Azure Machine Learning services, and applying Azure Data Science solutions in real-world scenarios. 070-774 exam measures the candidate's knowledge and skills in several key areas, including data preparation, feature engineering, selecting the appropriate models, optimizing and publishing the models, and using the Azure Machine Learning Workbench.
Reference: https://www.microsoft.com/en-us/learning/exam-70-774.aspx
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Microsoft 070-774: Perform Cloud Data Science with Azure Machine Learning exam is designed for individuals who are interested in leveraging Azure Machine Learning for data science tasks. Perform Cloud Data Science with Azure Machine Learning certification exam is intended for professionals who are looking to validate their skills in building and deploying machine learning models using Microsoft Azure. Passing 070-774 exam will demonstrate the candidate's ability to use Azure Machine Learning to design, develop, and implement machine learning solutions in the cloud.
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Microsoft 070-774 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Operationalize and Manage Azure Machine Learning Services | - Consume related Cognitive Services APIs - Deploy models using Azure ML - Consume ML models - Manage ML projects and workspaces |
| Use Other Services for Machine Learning | - Streamline development with existing resources - Perform database analytics using SQL Server R Services - Build/use neural networks (Microsoft Cognitive Toolkit) - Perform data sciences at scale via HDInsight |
| Develop Machine Learning Models | - Initialize and train models - Select appropriate algorithm/method - Validate models |
| Prepare Data for Analysis in Azure Machine Learning | - Import and export data to/from Azure ML - Cleanse data for Azure ML - Explore and summarize data - Perform feature engineering |
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