This page is entirely dedicated to providing useful resources about programming and data science that I have hand picked. So, if you are looking to get into these areas, or maybe you are already in but want to know more; you should definitely bookmark this page and give it a share too.
All the resources in the page are resources that I myself have read or used and recommend entirely off the value I got from them.
I will update this page regularly when I find new resources that I think are good. If you have any suggestions then get in contact with me and I will take a look at them. You can contact me via my blog’s contact form, by emailing me at firstname.lastname@example.org or by tweeting to me @jamal_moir.
Now I feel that I should start off by saying that this is a course you have to pay for. However, the quality of this course is outstanding and the knowledge you get from it is invaluable.
This course was created by Michael Kennedy whom you probably know from his popular podcast Talk Python To Me. It covers writing pythonic Python code, best practices and patterns; the kind of stuff that you don’t learn from textbooks and courses, but that you attain from years of experience. As I said, invaluable information.
You can read my review of this course here: Write Pythonic Code Like a Seasoned Developer; The Course Everyone New to Python Desperately Needs to Take
Becoming a Data Scientist [FREE]
This is a really motivating site ran by Renee. It’s chocked full of information and is not just a blog, but also a podcast and a study-group forum too.
The podcast is a really great gateway to take a look into how some influential data scientists have gotten to where they are. They talk about how they got into the field, how they acquired the skills they needed and give out plenty of advice. It’s really interesting listening to Renee talk to her guests and she handles the podcast exceptionally well.
Also, because the podcast and study-group start from the ground up, it’s especially good you beginners out there. You should definitely give the study-group exercises a go!
The Field Guide to Data Science is a really well put together book by Booz Allen Hamilton that focuses on how to approach data science problems rather than being a step by step guide on how to implement an algorithm or use a tool.
It is a real piece of eye-candy crammed full of bold graphics and well thought out typography. However the real attraction of this book is the information inside. It gives you insights into how to approach data science problems, how to think and while doing this enforces what they are preaching via the use of concrete anecdotes of how they have applied the presented point.
I think this book is better read after having some experience with data science as it uses a fair amount of technical terminology and talks about algorithms without explaining what they are or do. Nevertheless this is a great book to read and will advance your data science skill set.