Choosing roles

Guidance for choosing roles, which helps gauge the difficulty level of your course.

Amy Peterson avatar
Written by Amy Peterson
Updated over a week ago

Read the page that describes different roles that would apply to your potential audience and choose the ones that are the most likely to benefit from your course. Write a sentence about each role you chose to explain why that role is a good fit for the course, as well as the extra skills or prerequisite knowledge you are assuming learners that take the course will have.


The author of a course on cleaning data in R chose the Data Analyst and Citizen Data Scientist roles as their audience. Their reasoning for choosing Data Analyst is that cleaning data is a fundamental step of performing data analysis. They chose Citizen Data Scientist because being able to find and work with dirty data is important to do before beginning any modeling of your data. 


Can I choose multiple roles?

You should choose the roles that would be the best fit for the course and provide justification for each choice. Think critically about the learner objectives for the course, and what specific roles would benefit most from these skills. If your course seems like it would be suitable for everyone, that's an indication of a problem, as that may indicate a lack of clearly defined learner objectives. It is important to think about targeting your course towards a specific demographic. You cannot easily please both beginners and experts on a topic.

What if my course does not seem to match any of the listed roles? Can I choose other roles that aren’t listed?

If necessary, but please discuss with your Curriculum Manager first to decide whether or not it constitutes a realistic DataCamp learner profile.

How should I think about different axes of expertise?

To complete a course, the learners may need programming skills, statistics skills, and domain-specific knowledge - and the levels of each may be different within your course. For example, your course may require beginner-level programming skills but advanced statistical skills and intermediate domain knowledge. It can be useful to think about how the roles match up to your course on each of these axes.

What about learners’ mathematical skills?

Many DataCamp learners do not have a university-level mathematical background. That means that you cannot assume that the majority of learners will be able to understand complex mathematical equations.

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