Data Science – Useful Resources

By | 02/07/2017

As I count down the days to the start of the Data Science course I’ve been reading a lot of blogs, books and watching a lot of YouTube & Udemy courses.

Having not picked up a stats book for the last 15 years, it’s surprising how much I remember! OK, some of the granular detail was a little rusty and it took me a while to remember everything however it’s all coming flooding back!

Here’s a list of what I’ve either worked or am working my way through, hopefully it’ll help anyone in the same position:


Think Stats Exploratory Data Analysis in Python – Allen B. Downey and have a dummy data set to play around with

Probability Cheat Sheet – After you’ve brushed up on your stats, this is a great way to remember the key concepts

Udemy Courses:

Machine Learning A-Z – Part way through this, great course and makes it easy to understand with a level of statistics explanation behind each model. For both Python & R

AWS Certified Solutions Architect – You’ll need to deploy your code, spin up instances so a good course to take

AWS Certified Developer – Same as above with a Developer slant

The Python Mega Course – Easy intro to Python for the beginner

R Programming A-Z – Just on case you’re an R person rather than Python


Professor Leonard – Great mathematics lectures from the ground up. Aimed at Degree level I’m assuming but feels like A Level standard. Stats lectures in there also.

Stanford Machine Learning – Feels like a definitive Machine Learning series, intense but great set of lectures.