3 Main Areas for Learning

Let's review the 3 main areas of Data Science and apply them to my approach to Educational Data Science. It is important to note that the ability to communicate is an additional skill needed for effective data science and should be considered a vital skill in all of the 3 Main Areas of Learning.

Substantive: I would define this into 2 main branches
1. Teaching
2. Learning

Mathematic and Statistics: 2 branches
1. Math: understanding the math behind the statistic is crucial to understanding your data
2. Statistical: Both in theory and in application. This includes an understanding of spreadsheets, charts, and graphs.


Technical (rather than "Hacking"): Several Branches
1. Basic Technology Skills: Skills such as computer fundamentals, keyboarding, word processing, spreadsheets applications, presentation skills, online best practices, and graphics

2. Programming: Such as Python and JavaScripting come to mind

3. Database: Both theory and application specific

4. Design


Question: So how to translate this model for my own learning? 

Conclusion:  
I need a plan that includes learning experiences in each of these 3 main areas
I need to practice communicating