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What is Data Science?


Data Science is doing some steps to create Inference or Prediction about an event using data.
 
Similar to creating a delicious Sandwich

What we want to talk about in this blog?


Data Science is an interesting area in 21 century. The trend for it is increasing. The Salaries are fantastic. It has prestige. And a lot more things. Also, there are a lot of websites and videos teaching about it. But all of them lack something. They don't make you learn based on your level of knowledge or if they do they are too long.
Here I tried to put data science with R in different levels so that in each level you will learn the end-to-end path.


What do you need to know for Data Science?


Knowledge of Cooking/Analytics and Creativity,
Following some Recipe/Steps
Using some Kitchen Tools/a Language or Platform ( R Programming Language)


How to do a data science project?


There are some Steps(Import raw data to R, Tidy, Transform data, Visualize data, Model data, Share result) to be done by R language(Main libraries: Tidyverse, Tiymodel, Rmarkdown, Shiny) using your Knowledge(Business Domain, Statistics, Statistical/Machine Learning, and Math) and Creativity.

A good example of steps is that if you want to make the food you need to buy material(Import), prepare(Tidy and Transform), cook(Model), assemble pieces(Visualize), and serve consumers(Share ).

A part of R language is tidyverse Library that everything even a little modeling, but tidymodels library, is the main library for Statistical/Machine Learning models. Also, your job in practice does not mean anything until you share with the people who can decide base on your analysis. This part is done by rmarkdown and shiny libraries.

If you don't know any of the things I mentioned that is completely normal. Actually, you are here to learn or remember them. So no worries. 

Here is the diagram of what I explained:
 Hexbins are R language libraries(), texts in blue are steps for a data science project, and each rectangular includes pieces of related steps.


How this blog is going to help you?


The full list is as below:


1- You learn R base codes (As Quick as possible)
2- You learn Starter                   level of Full data science Steps 
3- You learn Beginner               level of Full data science Steps 
4- You learn Elementary               level of Full data science Steps 
5- You learn Intermediate             level of Full data science Steps 
5- You learn Upper-Intermediate level of Full data science Steps 
5- You learn Advanced                 level of Full data science Steps 
5- You learn Proficient                 level of Full data science Steps 

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