Read the page of sample learner personas and choose 1 or 2 of them as the most likely to benefit from your course. Write a sentence about the ones you chose stating how good a fit you think they might be. In brief, the five personas are:

  • Unaware Umberto: is new to statistics, programming, and the domain he's working in.
  • Starting Sindhu: has domain expertise, but not as much programming or statistics.
  • Coder Chen: is a strong programmer, but lacks domain expertise and statistical background.
  • Mathematical Marta: strong mathematical and statistical background, a little programming, completely new to the domain.
  • Advanced Alex: has all three kinds of knowledge.

Note: the full description of these personas mention specific technologies or domains, such as Python or epidemiology. When using these personas, replace these by equivalent levels of knowledge about technologies or domains appropriate to your course, e.g., novice understanding of R but advanced understanding of medical imaging.

Examples

  1. The author of an introductory course on data visualization with Python chose Marta, Sindhu, and Umberto as her audience. Her reasoning is that Chen and Alex (who are both strong programmers) will be able to pick up the programming on their own without a course, but the other three all need a course to show them how code can create pictures.
  2. The author of a course on RNA-Seq analysis decided that her target audience included people who know biology but are lacking R and/or statistics. Therefore, she picked Sindhu as the main learner persona for her course, and Alex as an additional persona.

FAQs

Can I choose more than two personas?

You can comment on how good a fit the other personas would be for your course, but if your course seems like it would be suitable for everyone, that's an indication of a problem. It is important to think about targeting your course towards a specific demographic. You cannot easily please both beginners and experts on a topic.

Can I invent my own personas?

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

Think about different axes of expertise

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

Overestimating students' mathematical skills

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

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