You are a data scientist at your company and you are assigned to several ML projects.
Therefore, you need to be able to create ML experiments and to run them on compute resources.
There are different roles that can be used for performing tasks on workspaces.
Which predefined role fits best for your tasks?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: C.
Option A is incorrect because Azure ML workspace comes with three default roles: Owner, Contributor, Reader.
There is no such a predefined role as Data-scientist.
Option B is incorrect because the Reader is one of the three default roles which are created while a workspace is created.
As its name suggests, it only provides read privileges to workspace objects, i.e.
it isn't sufficient for data scientists who want to create and run experiments.
Option C is CORRECT because the Contributor role provides users with the ability to create experiments, attach computes, run experiments and deploy web services, but also enables creating/deleting compute resources.
It is stated that you need to work on predefined computes, this is not the best option for your role.
Option D is incorrect because the Owner role grants full access to the workspace, which, in a large organization, should be limited to certain users, not to be exposed for those who only need user-level privileges.
Reference:
In this scenario, as a data scientist, you need to create and run machine learning experiments on compute resources. Therefore, the predefined role that best fits your tasks is the "Data Scientist" role.
The "Data Scientist" role is designed to provide data scientists with the ability to perform tasks such as creating and running experiments, managing data sources, and creating and publishing models. This role provides full access to the workspace and its associated resources.
The other predefined roles, "Reader", "Contributor", and "Owner", do not provide the necessary level of access and permissions for a data scientist to perform their tasks.
The "Reader" role only allows users to view resources and data, but not to make any changes or perform any tasks. The "Contributor" role allows users to make changes to resources, but does not provide access to all resources in the workspace. The "Owner" role provides full control and access to the workspace and its resources, but may not be necessary for a data scientist who only needs to create and run machine learning experiments.
Therefore, the "Data Scientist" role is the most appropriate predefined role for a data scientist who needs to create and run ML experiments on compute resources.