In this blog, I am trying to provide some idea about data science skill as well as technologies.
- First, you will get some logical representation about data science skill map
- Second , idea about different technologies.
- Finally, some important theory base knowledge which is must for any data scientist to understand the concept.
Understanding Data Science Skills
In this above diagram, I have tried to mention the key skill areas in the data science field.
In data science, there are three skill areas; technology to problems, predictive analytics and software engineering. There are different processes/items which are involved, like prioritizing projects, visualization & communication, product analytics, business optimization, data and machine learning.
Finally, performing all the processes, we will get the below insights
- Deliver business insights
- Deliver ML prototypes
- Build data products
Technologies for Data Science
To learn data science, there are different technologies. Here is one graphical representation. I found this usefull information from one of the data science tutorial.
We should get the knowledge about mathematics and statistics.
Other than these above things, we need to understand
- A/B testing
- Hypothesis testing