Q:

How do I get started in astronomy data analysis?

I am learning some machine learning (I have previous background in statistics) on my own, and I am interested in getting some hands-on practice by doing some ML analysis in R and Python. 
Given how mad I am about astronomy, I would love to get my hands dirty on doing some ML using open data. I am aware that organisations like NASA have lots of open datasets. What I am less clear about is the kind of analysis that needs to be done. 
So, I'd like to know if there is any website where I can get a repository of space data (images, signals, whatever) and which asks what analysis is required; kind of like Kaggle where one gets the dataset and has the required question which one can attempt.

A:

A possibility might be a course at a university, youtube, or a self-study-course via a book.
What we've used in our astrostatistics class was "Wall & Jenkins: Practical Statistics for Astronomers" which presents theoretical sections with exercises as follow-ups. No answer sections exist, as you need to do some programing for some of them.
But you can maybe lend this or similar books at a local university library, without the need to spend money.

