Here's some free book lists

http://www.kaggle.com/wiki/Tutorials

http://metaoptimize.com/qa/questions/186/good-freely-availab...

I think the best single resource is Kevin Murphy ML text, but there's lots of relevant stuff on linear algebra, Bayesian analysis etc

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Here's a "curriculum"

http://blog.zipfianacademy.com/post/46864003608/a-practical-...

And look at the coursera courses by Koller, Andrew Ng, NLP by Collins etc

There is a comprehensive list of online resources that we put together on our blog: http://blog.zipfianacademy.com/post/46864003608/a-practical-...

This is a free version of the book "Mining Massive Datasets".

Basically statistical methods that work with big datasets, which is the core of data science.

http://infolab.stanford.edu/~ullman/mmds.html

Thanks I was expecting may be a series of books, lectures, video which can take me from novice to intermediate level in data science.

I am willing to spend 10 hours a week on this.

This seems to fit the bill: https://www.coursera.org/course/datasci

I did the first two weeks of this course and found it quite accessible, although the second week question of implementing matrix algebra in SQL didn't seem to have much preparatory material in the lectures. Unfortunately I've had to drop out due to a concussion, but I think that most HN'ers would be able to take this course.