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Updated: Sep 23, 2026
No. of Questions: 40 Questions & Answers with Testing Engine
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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Analyzing Big Data with Microsoft R |
| Exam Number: | 70-773 |
| Related Certifications: | MCSA: Machine Learning Microsoft Certified Professional |
| Exam Price: | 165 USD |
| Available Languages: | English |
| Exam Duration: | 150–180 |
| Real Exam Qty: | 40–60 |
| Certificate Validity Period: | Retired, no longer active |
| Exam Format: | Case studies, Multiple choice, Drag and drop, Multiple answer |
| Passing Score: | 700 out of 1000 |
| Recommended Training: | Microsoft Official Course 20773: Analyzing Big Data with Microsoft R |
| Exam Registration: | Microsoft Exam Registration |
| Sample Questions: | Microsoft 70-773 Sample Questions |
| Exam Way: | Online proctored or at authorized Pearson VUE test centers |
| Pre Condition: | Basic knowledge of R programming, statistics, data structures, and familiarity with SQL Server, Hadoop, or big data platforms |
| Official Syllabus URL: | https://www.microsoft.com/en-us/learning/exam-70-773.aspx |
TrainingQuiz expert team recommend you to prepare some notes on these topics along with it don't forget to practice Analyzing Big Data with Microsoft R 70-773 Dumps which been written by our expert team, Both these will help you a lot to clear this exam with good marks.
Reference: https://www.microsoft.com/en-us/learning/exam-70-773.aspx
| Section | Weight | Objectives |
|---|---|---|
| Explore and Visualize Data | 20% | - Summarize and aggregate data - Perform exploratory data analysis - Create visualizations using R and RevoScaleR |
| Evaluate and Optimize Models | 20% | - Assess model performance - Tune model parameters - Optimize R scripts for scale and speed |
| Deploy and Operationalize R Solutions | 15% | - Integrate R with SQL Server R Services - Manage scalable analytics workflows - Run R scripts in Hadoop/Spark environments |
| Manage Data Sets | 20% | - Handle large datasets beyond memory - Read and write data using Microsoft R Server - Transform and clean data |
| Build Statistical and Machine Learning Models | 25% | - Train linear and generalized linear models - Use partitioning and parallelized models - Process text data with RML packages |
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