I met a friend on the train one morning and he expressed an interest in data science. I said I'd send him a few loinks to usefule resources, but instead I wrote up an article because I felt I needed to ramble on about things I've found useful and not so useful. Hope some of this helps.
There are more books about data science out there, but they are heavily intertwined with the Python programming language.
In that respect, it tells you a bit about how it is hard to separate Data Science and Python as it feels like Python is an extremely common tool that is used to apply the theory of Data Science.
This first book though, gives a good overview of Data Science, Python and the maths involved.
Hello World by Hannah Fry
I have read this book, and have been to see Hannah Fry talk about this too. It's a popular science book that gives a good overview of the applications of algorithms, data anlaysis and machine learning, mainly through anecdotes and examples but without getting bogged down in any mathematical detail.
The Art of Statistics: Learning from Data by David Spiegelhalter
This book is excellent! It taskes real world situations and questions and tells you about how to go about answering them. Whilst explaining everything, the author manages to not get bogged down in the details either, allowing you to read and absorb the theory. Well worth the money!
To compliment Hello World, this is Hannah Fry's eight-part podcast about the work she has done at DeepMind around Artificial Intelligence.
If you're thinking of entering the Data Science world, you're almost definitely going to need to use the Python programming language at some point. It's a very beginner friendly language, and the community around it is superb. As such there are some great podcasts, like this one. Not all episodes are on Data Science, but here are some that are, and the careers one in particular shows that you don't have to be a young, gifted, mathematical programmer to pursue it.
Both of these episodes are related to the opportunities and applications that Python can help you get in to, but you don't need to know Python to get anything out of them.
For me, I enjoy listening to these, but it helps me focus on what I'm doing this for. Do I want to work doing Data Science for a big organisation? Maybe not. But I might like to explore it to some level and see where it takes me. I'm not 21 having just graduated. I'm nearly 44 with a family and responsibilities, so perhaps using Data Science to write blog posts on the stats behind news articles, political manifestos, the form of a Football team, or how crazy it was that Kylie's first 7 singles reached the number 1 or 2 in the UK singles chart, is as far as I want to go.
If I had the time and the money, I'd probably do the OU's BSc in Data Science. It's got all the mathematical theory and data analysis subjects that would give a solid foundation on which to build a Data Science career.
But, as much as it's the Daddy of resources, it'd probably cost around £18,000 to do!
I live in the UK near London, and CityLit is like an adult education college. Not so useful if you live outside the UK or even if you do live in the UK and can't go to London.
I like CityLit! Their approach is quite gentle, non-academic and they just seem interested in delivering manageable chunks of knowledge for a relatively low price. It doesn't suit every subject, but if you want an intro to Data Science, they do a few courses. They're mainly introductions, but there are a few that stand out if you're completely new.
- Probability and Statistics for Data Analysis
- Linear Algebra and Optimisation for Machine Learning
- Data Analytics with Python: Introduction
None of these course will make you an instant Data Science Guru, but just might get the ball rolling.
I have done CityLit courses because more than anything, with a job and family, these courses buy you time with other human beings with a similar interest and at least one human being who knows the subject matter.
When I did a 6 week animation course, it bought me 18-hours of time in a class room. I would never find 18 hours over 6 weeks at home to dedicate to study.
Maybe I've written too much about this, or over-estimated your interest, but it's a vast topic with so many misconceptions. If you've got an interest in Data Science, there is quite a broad target to aim for, and some of the technical sides of it are smaller bumps in the road than you first think.
Hope it helps :-)