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.

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.

  1. What problem(s) will students learn how to solve?

  2. What are the learning objectives of the course?

  3. What technologies, packages, or functions will students use? For BI courses, this will most likely consist of DAX functions and services like Power Query Editor.

  4. What terms or jargon will you define?

  5. What analogies or heuristics will you use?

  6. What mistakes or misconceptions do you expect?

  7. What datasets will you use? A few notes on this...

    1. 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.

    2. Make sure the datasets you use are available for commercial use.

    3. Datasets used in previous Power BI 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.

    4. Each individual dataset behind a Power BI workbook 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. The total size of all datasets (Fact + Dimension tables) behind a workbook should be a maximum 20MB.

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 are unsure about this, make sure to discuss prerequisites with your Curriculum Manager.

Step 3: Course outline

The course outline describes the flow of the course on a lesson-by-lesson basis. In the course outline, instructors are required to write a learning objective for each lesson along with the concepts and functions that will be used in the interactive exercises to achieve that learning objective.

Step 4: Capstone exercises

Capstone exercises are the final exercises of each chapter and should showcase how far learners are likely to get during a chapter. Capstone exercises help determine the scope of a chapter and help us identify potential technical issues early on in development, which helps keep our course launches on track.

Step 5: Build ONE complete lesson in the Teach editor

During this step, instructors will build a full lesson using DataCamp's course editor, Teach. 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 6: Revisit course outline

This step is to encourage instructors to revisit the outline they've built as they will have a clearer idea of the possible scope of a DataCamp course. This is the ideal time to revisit the outline and update it if necessary.

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