Pass your actual test with our Microsoft 070-774 training material at first attempt
Last Updated: Aug 11, 2026
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Microsoft 070-774 certification is highly valued in the industry, as it represents a high level of expertise in cloud data science using Microsoft Azure. It can open up doors to many career opportunities, such as data scientists, data analysts, machine learning engineers, and cloud architects. Additionally, it serves as proof of the candidate's ability to leverage innovative technologies to turn data into actionable insights that drive business success.
Microsoft 070-774 certification exam is designed for individuals who want to demonstrate their proficiency in performing cloud data science tasks using Azure Machine Learning. 070-774 exam verifies a candidate's ability to use various Azure Machine Learning tools and services to develop and deploy machine learning models in a cloud environment.
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The Microsoft 070-774 exam covers a range of topics including data exploration, feature engineering, model training and evaluation, deployment, and operationalization. Candidates are expected to demonstrate their ability to use Azure Machine Learning to build end-to-end predictive analytics solutions, integrate with other Azure services, and manage the lifecycle of machine learning models. Successful completion of 070-774 exam will earn the candidate the Microsoft Specialist: Azure Machine Learning certification, which is recognized by employers as a valuable credential in the field of data science and machine learning.
Reference: https://www.microsoft.com/en-us/learning/exam-70-774.aspx
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare Data for Analysis in Azure Machine Learning | 30% | - Import and export data
|
| Topic 2: Develop Machine Learning Models | 35% | - Validate and evaluate models
|
| Topic 3: Use Other Services for Machine Learning | 10% | - Integrate with HDInsight - Work with Microsoft Cognitive Toolkit - Leverage Cortana Intelligence Gallery - Use SQL Server R Services |
| Topic 4: Operationalize and Manage Azure Machine Learning Services | 25% | - Manage workspaces and experiments
|
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