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Perform Cloud Data Science with Azure Machine Learning 70-774 Exam
Perform Cloud Data Science with Azure Machine Learning 70-774 Exam is centered around Azure Machine Learning, Bot Framework, and Cognitive Services. The exam is designed to target candidates who are Data Scientists or Analysts using the Microsoft Azure cloud services to build and deploy intelligent solutions. This exam will test your understanding and familiarity with common data science processes such as filtering and transforming data sets, model estimation, and model evaluation. Machine Learning is one of the hottest topics and technologies in the industry right now.
Machine Learning is being used to combine with Big Data to automate the processes of gaining insights and predicting future behavior of systems, devices, and people. In an effort to expand out the breadth of certifications and exams offered around Microsoft Azure and the cloud, Microsoft has added the Perform Cloud Data Science with Azure Machine Learning Microsoft 70-774 Exam. This exam only available for the candidates till 30th June 2019 after that this may get replace with some other exam so you can plan get it completed before it get expire.
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This is the list of the contents in our Perform Cloud Data Science with Azure Machine Learning 70-774
- Perform data sciences at scale by using HD Insights
- Explore and summarize data
- Cleanse data for Azure Machine Learning
- Azure Machine Learning models
- Import and Export Data to and from ML.
- Validate models
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Overview about Overview about MICROSOFT 70-774 Exam
- Registration Fee: 165 USD
- Number of Questions: 40-60
- Length of Examination: 120 minutes
- Format: Multiple choice, multiple answer
- Passing Score: 70-80%
Microsoft 070-774 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Operationalize and Manage Azure Machine Learning Services | - Consume ML models - Consume related Cognitive Services APIs - Deploy models using Azure ML - Manage ML projects and workspaces |
| Develop Machine Learning Models | - Initialize and train models - Validate models - Select appropriate algorithm/method |
| Prepare Data for Analysis in Azure Machine Learning | - Cleanse data for Azure ML - Import and export data to/from Azure ML - Perform feature engineering - Explore and summarize data |
| Use Other Services for Machine Learning | - Perform data sciences at scale via HDInsight - Streamline development with existing resources - Perform database analytics using SQL Server R Services - Build/use neural networks (Microsoft Cognitive Toolkit) |






