Data Science

There are a lot of resources online to learn data science. Currently, there are 3 primary languages used in the data science community - R, python and SAS. The first two are open source and are hence gaining rapid adoption but the last one is still widely used in medical systems. If you are conflicted between choosing R and Python here is a good resource that can help you choose.

Basics of data science:

  1. r4ds or R for data science is a book that teaches the basics of data science using R and particularly, a set of libraries in R called as the "tidyverse". An extremely accessible and incredibly handy resource that any beginner will benefit from. Though it teaches R libraries, the fundamentals apply to any language and data science in general! It also has a community if community driven learning and a place to discuss your learning sounds good.
  2. If you like learning by doing and what is called as interactive learning, datacamp has a huge catalogue of bite sized courses and learning tracks that can help you navigate data science. Datacamp is taught by experienced professionals and content creators and can be really beneficial if a few minutes of video and lessons followed by actual coding to accomplish a task to reinforce the learning, sounds like something that you might want to do. Typically, a susbsription is needed for personal use but a classroom subscription is entirely free if you can get it. Has courses for both R and python and a few courses on SQL, Git and Shell. Recommend learning just the basics of data science - data wrangling, tidying, etc. here and using other resources as you level up.

Machine learning/Deep learning

  1. Fastai is hands down the best resource on the internet to learn machine learning and deep learning from. A heavily application focussed teaching method that gets you started on problems from the get go, you can learn cutting edge techniques to achieve state of the art results for any of your problems.
  2. Andrew Ng's Coursera courses for machine learning and deep learning are tried and tested and you cannot go wrong with them.