Pass the DP-100 Exam
Understand various Data Science concepts for Azure engineering
Understanding various Azure resources to use in solving different Data Analytics problems
Learn how to use Microsoft Azure Documentation and other online resources for understanding and implementation of various tasks required for Data Science
Note: This course is designed for students who want to attain the “Microsoft Certified: Azure Data Scientist Associate” certification
This practice test contains specially curated question which will test your knowledge and give you 100% confidence in clearing DP-100 examination. The question being asked are created directly from Azure Documentation or present an application of data engineering scenarios.
These questions are backed by through explanations and links to Microsoft documentation from where the question was framed. By taking these test you will be confident in facing any kind of questions asked in the DP-100 Designing and Implementing a Data Science Solution. The tests are regularly updated with the addition or removal of topics in the testing areas by Microsoft.
Why take Microsoft Certified: Azure Data Scientist Associate certification
Azure Data Scientist helps in deducing highly valuable information from raw data using the high-performing, efficient, organized, and reliable services provided by Microsoft Azure, given a set of business requirements and constraints. They deal with a large amount of data that needs to be organized, filtered through and use mathematical solutions to obtain Insights regarding the data. They also design, implement, monitor, and optimize data platforms to meet the Machine learning pipelines needs.
All questions have a detailed explanation and links to reference materials to support the answers which ensures accuracy of the solutions.
The objectives covered in this course are
- Manage Azure resources for machine learning(20-25%)
- Run experiments and train models(20-25%)
- Deploy and operationalize machine learning solutions(35-40%)
- Implement responsible machine learning(5-10%)
Candidates for this exam should have subject matter expertise integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building Machine Learning solutions, alongside with the knowledge of data processing languages such as SQL, Python, or Scala, and they need to understand parallel processing and data architecture patterns.
“All the best for your exam”
