Advice on self-study for my winter break?

Hello everyone,

I'm a math major interested in getting into data science. I took a seminar on data science this semester (ending in 2 weeks) and it was entirely on data mining/python/data cleaning/visualization etc.

I want to spend my winter break of 6 weeks studying machine learning and just getting a deeper feel of the subject. I don't like video lectures and I kinda poked my head into "The Elements of Statistical Learning" but I feel like it may be just a little bit over my head (only on page 18).

I'm an experienced python programmer (with understanding of basic data structures/algorithms/complexity) and have taken the following math courses:{calc 3, intro linear algebra, intro probability, intro real analysis}. Is there a book or pdf that I can read and finish in 6 weeks that will give me the theory of machine learning in some sort of nutshell?

Should I just put my face into The Elements of Statistical Learning for 6 weeks (it's not undoable, just seems kinda slow) or do you have a better book recommendation?

Oh and I think I can only manage 400-500 pages in 6 weeks (Elements is like 700+).

I have the practical side covered with the book "Building Machine Learning Systems with Python" so only theory recommendations please and thank you!