This is an interesting TED talk by Prof. Rebecca Nugent at Carnegie Mellon University.
Many people think that they are not good friends with math or statistics, and data science is something that's far removed from them.
She points out that people might have wrong self-perception on their own skill sets, especially on statistics and math.
We all actually make probability and statistic based decisions every day although we are not aware of this. She gives examples of data science in our daily life.
Data science doesn't necessarily mean fancy machine learning and advanced computer science skills.
The diagram above defines data science (taken from her slides).
The key idea of data science is communication and collaboration across disciplines.
For example, at EdLab, our research (I've been involved in so far) have been all data science problems.
The entire processes --- defining research questions, defining and collecting data, pre-processing data, and conducting statistical analyses --- have always been based on collaboration among different teams, (e.g. development, experience, and research). And all the steps were conducted in iterative ways.
So, again, data science is this entire iterative process based on collaboration, not just machine learning or AI.
I think this video is very useful in understanding the concept of data science and think about the examples related to data science in our daily life.
Also, of course, it would be interesting to think about data science problems we are facing here at EdLab. Please share if you have any ideas about this!