Reddit reviews Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies (The MIT Press)

fundamentals of machine learning for predictive analytics

Working through a chapter a night after work. Mostly for the terminology help. It does a great job of using real world examples about how you should attack problems and how to communicate with business stake holders. Its not really about the mathematics behind everything more about how to communicate it within the business.

Depending on what you want to learn:

PYTHON SPECIFIC

You mentioned building websites, so check out the flask mega tutorial. It might be a bit early to take on a project like this after only a month, but you've got time and learning-by-doing is good. This'll teach you to build a twitter clone using python, so you'll see databases, project structure, user logons etc. Plus he's got a book version, which contains much of the same info, but is good for when you can't be at a computer.

The python cookbook is fantastic for getting things done; gives short solutions to common problems / tasks. (How do I read lines from a csv file? How do I parse a file that's too big to fit in memory? How do I create a simple TCP server?). Solutions are concise and readable so you don't have to wade through loads of irrelevant stuff.

A little while down the road if you feel like going deep, fluent python will give you a deeper understanding of python than many people you'll encounter at Uni when you're out.

WEB DEV

If you want to go more into web dev, you'll also need to know some HTML, CSS and Javascript. Duckett's books don't go too in depth, but they're beautiful, a nice introduction, and a handy reference. Once you've got some JS, Secrets of the javascript ninja will give you a real appreciation of the deeper aspects of JS.

MACHINE LEARNING
In one of your comments you mentioned machine learning.

These aren't language specific programming books, and this isn't my specialty, but:

Fundamentals of Machine Learning for Predictive data analytics is a great introduction to the entire process, based upon CRISP-DM. Not much of a maths background required. This was the textbook used for my uni's first data analytics module. Highly recommended.

If you like you some maths, Flach will give you a stronger theoretical understanding, but personally I'd leave that until later.

Good luck and keep busy; you've got plenty to learn!

I have this book, and it has been really useful for learning the theory and math behind many of the main ML models: https://www.amazon.com/Fundamentals-Machine-Learning-Predictive-Analytics/dp/0262029448/ref=sr_1_2?ie=UTF8&qid=1499437032&sr=8-2&keywords=machine+learning+mit

Worth having in my opinion!