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Genre: eLearning
Designing and Implementing a Data Science Solution on Azure (DP-100)
The Azure Data Scientist applies their knowledge of data science and machine learning to implementing and running machine learning workloads on Azure; in particular, using Azure Machine Learning Service. This entails planning and creating a suitable working environment for data science workloads on Azure, running data experiments and training predictive models, managing and optimizing models, and deploying machine learning models into production.
Part of the requirements for: Microsoft Certified: Azure Data Scientist Associate
Skills measured
The content of this exam was updated on May 22, 2020. Please download the exam skills outline below to see what changed.
Set up an Azure Machine Learning workspace (30-35%)
Run experiments and train models (25-30%)
Optimize and manage models (20-25%)
Deploy and consume models (20-25%)
To prepare for the exam, we strongly advise you to attend the training courses, review the study material, and gain hands-on experience related to the topics covered in the exam.
We tried our best to provide correct answer of questions in this course, however we strongly request you to do research for correct answer too instead of just blindly memorize the answers.
Who this course is for:
The students or professionals who have successfully completed the training of Home / Microsoft / Designing and Implementing a Data Science Solution on Azure (DP-100T01) Designing and Implementing a Data Science Solution on Azure.
The students or professionals who have a fundamental knowledge of Microsoft Azure.
The data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.
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