Course README template
Each DataCamp course has an associated GitHub repo. We use the README in each course repo as the course blueprint or course spec, as we often call them. The course spec is used to plan a course during the course design phase and is used as a reference during course development. The following gives a brief explanation of the Course README and its sections. Each section is linked to a longer and more in-depth article on that step of the course spec. Please keep in mind we have a 500-word maximum for Scripts.
Step 1: Brainstorming
The initial step of the course design process is to have the instructor think about all the things their course could be. This step is meant to get ideas written down and not necessarily all of the ideas written in this step will be included in the final course.
What datasets will you use? A few notes on this...
One dataset per chapter is typical. Some courses use a single dataset throughout. In this case, it has to be a reasonably rich and interesting dataset to keep the student's attention over the whole course. You can use multiple datasets in each chapter, but you have to be careful that they don’t require too much time to introduce and explain.
Make sure the datasets you use are available for commercial use.
Datasets used in previous Cloud courses should be avoided. This is to help keep learners engaged with new scenarios and problems. If you’re having trouble finding datasets, take a look at the following article.
Each individual dataset should be a maximum 10MB. This is significantly smaller than most datasets, but it reduces the lag for students taking the course on a virtual machine and shouldn’t have any influence on the exercise.
Step 2: Who Is This Course for?
During course design, it is crucial to determine the level of the course. Is this course for beginners or more advanced students? Does this course require statistical knowledge? This helps determine the course difficulty, which helps define the course's scope. If you need clarification on this, discuss prerequisites with your Curriculum Manager.
Step 3: Course outline
The course outline will most likely be the most time-intensive process of the Spec phase. When building the course outline, we will ask you to define every lesson in the course.
What learning outcomes will be covered in the lesson’s video? What is your plan for the three exercises associated with that video? What learning outcomes and skills will those exercises cover? How will you test the learner’s understanding of those skills? What types of exercises (i.e. multiple choice, Cloud exercises, etc) will your lesson contain?
This step is especially important for us to discover potential blockers in the capability of cloud exercises. You may propose a Cloud exercise that is not technically feasible; we will want to iterate on these ideas before implementing the course.
Step 4: Build ONE Video and One Associated Exercise in the Teach editor
During this step, instructors will build use DataCamp's course editor, Teach, to build one video and one exercise. This step allows both the Curriculum Manager and the Content Developer to review the instructor's work and determine possible pain points early in the process to ensure fluid course development.
Step 5: Revisit course outline
This step encourages instructors to revisit the outline they've built. This will give them a clearer idea of the possible scope of a DataCamp course. This is the ideal time to revisit and update the outline if necessary.
Step 6: Write Course Description and List Course Prerequisites
The last step of the Course Spec process is to put the Course Description and Course Prerequisites into Teach.