DataCamp for Mobile
DataCamp for Mobile allows students to engage with their data science learning content anytime, anywhere (even on the toilet).
A course is clearly subdivided into chapters and lessons. A mobile course consists of 4 to 5 chapters, each mapping to one major concept of a course (eg "Plotting in Matplotlib" or "SELECT clause"). Each chapter in turn consists of 2 to 5 lessons (eg "Histograms" or "the COUNT() function"). Each lesson comprises 8 to 15 exercises, which are the fundamental building block of mobile content.
This philosophy of using the exercise as an exclusive building block distinguishes mobile content from desktop content. Rather than alternating between exposition (in the form of videos or written lessons), and interactive exercises, exposition should be kept to a bare minimum - always prefer showing over telling.
The last lesson in every chapter is a practice lesson, which is 10 - 25 exercises. The only material difference between a practice lesson and a course lesson is that practice lesson exercises usually provide little to no background context, and should theoretically be doable by anyone who has completed the course lessons in a given chapter. Practice lessons presented to students in a random order (in contrast to course lesson exercises, which are always shown in the order specified in their YAML files). These pools of practice content are currently embedded within courses, but will eventually be extracted into a full practice-only mode, as well.
Where do I start?
First, go through the development process documentation to get set up with your course repository and development tools.
Then, set up the structure of your course repository according to the documented repository structure.