Preparing for data science interview in R and python I'm preparing for a data science interview. The main languages the organization uses are Python and R. I am familiar with those languages; I do regressions, t-tests, data visualizations in them. However, I often use Stata as it's usually more convenient for what I want to do.
Is there any website that can help me get these two languages at my fingertips (especially advanced functions) for these interviews? (For example, if I were learning SQL, I would go to SQLzoo)
 A: I was a hardcore stata user myself during university (studied econometrics). Im working as a Data Scientist right now and I asked myself the same question not long ago. 
Im gonna be honest. You can read all the books you want. What really will boost your skills with any programming language (and will help you the interview aswell) is to actually work and at first mostly struggle with it. I would recommend you to grab a Dataset from Kaggle and to perform a simple analysis using R and Python. Afterwards build some predictive model and see how you compare to all the other solutions.
This is what helped me the most. Reading was...good...but the real boost came from all the kaggle competitions (Try https://www.drivendata.org/competitions/ if you want to do some good :)) I participated in. 
Nonetheless, here are some books I used:
For R I only used introduction to statistical learning and ALOT of stack overflow :D
But a good list of books for both languages can be found here: https://advanceddataanalytics.net/ebooks/
Python: I really enjoyed 
Data Science from Scratch
First Principles with Python
As well as:
Python for Data Analysis by Wes McKinney
Hope this helps :)
With kind regards,
Alex
A: I suspect what would be more helpful than trying to learn a bunch of analyses in R or Python would be to determine the kind of analyses that you would be likely to perform in this position.  Understand what the organization does, what kind of data they are likely to have, and how you could benefit the organization by bringing your skills.  
Maybe try to think in terms of broad categories of data science.  Like performing simple tests and regressions on small data sets, data mining, or machine learning.  Which would be applicable for this organization?
Also, if there is a certain subject matter, looking up the R packages in that field are helpful to get a sense of what kinds of issues that field deals with.  R has packages that are specific for e.g. psychology, fisheries, economics, or agriculture.  They really do use approaches specific for their field.
What is the organization trying to accomplish with this position, and how can you help them accomplish this?  Is it about improving profitability, reducing workplace accidents, improving marketing, scientific research?  What question would help achieve this, what data would you need, how would you get the data, what analysis would you perform?
I think you will have to think through these questions to have sense of where to begin whatsoever.  There are simply too many types of analyses too learn and too many packages available in R to try to learn it all without narrowing down what you are trying to learn about.
It might also be helpful to look up in what situations people use R and in which people use Python.
You might also think about how you would work with others in the organization, and your philosophy on testing code, making readable code, having code double-checked by others.  I believe there was some discussion on these topics in the July 23, 2017 and July 16, 2017 episodes of this podcast: Linear Digressions podcast.
A: there are many resources for python
https://pythonprogramming.net/
This website has a lot of hands-on small projects
