If you are just starting to code in R or Python or would like to improve your coding skills, check out my top coding resources and tools for beginners (and not so beginners!).

Of course, here at Biostatsquid you can also find guided tutorials and step-by-step guides to learn how to code in R and Python. Don’t forget to check out my Youtube channel to code and analyse data with me!

Here are some of my favourite resources that really helped me get into the coding world!


I cannot recommend Datacamp enough! This amazing platform has a wide range of courses for R, Python, Shell, SQL and Spreadsheets. The courses consist of short videos and interactive exercises, and they don’t require anything to be installed, you only need a web browser. Some of the introduction courses and the first chapter of every course are free, to access the rest of the content you need to pay a subscription.

If you are only just starting to code in R, or would like to brush up your R skills, be sure to check:

  • Introduction to R for Biologists.  This course has been designed to introduce biologists to R, showing some basics, and also some powerful things R can do (things that would be more difficult to do with Excel). The aim is to give beginners the confidence to continue learning R, so the focus here is on tidyverse and visualisation of biological data.
  • Computational Genomics with R. I recommend this free online book-tutorial to all levels, it is absolutely brilliant! Starting from R basics to complex statistical tests and machine learning, it also covers many different types of bioinformatic analysis, from RNAseq, to ChIP-Seq, to genomic intervals… It’s really nicely explained if you are new to the topic or the method.
  • This blog post offers a great explanation of RStudio Projects and Working Directories. If you are a beginner in R, it will help you structure your scripts in a much cleaner a code-efficient way, if you are already used to R, you might still learn a few new coding skills to improve your code!
  • Additionally, you might want to check out this other post on Project Management with RStudio. This great guide includes many tips and tricks to make your code more reproducible, and shares some of the best practices for project organization.
  • Guru99 also has some nice tutorials and explanations. It offers a complete course on R for beginners and covers basics to advance topics like machine learning algorithm, linear regression, time series, statistical inference etc.


I need to brush up on Python coding tools and resources! I learnt Python through Datacamp courses (I promise I am not sponsored in any way by them, they’re just amazing!) and through The Data Science Course 2023: Complete Data Science Bootcamp course from Udemy. This last one was great to get a better understanding of statistics concepts and machine learning, and to learn how to code in Python from scratch! 100% recommended!

I haven’t tried it yet, but I have heard great things of Rosalind, a platform for learning bioinformatics and programming through problem solving.


Galaxy Training has a lot of tutorials on transcriptomics, genomics, metabolomics… but also machine learning and statistics. It’s really great to start off with a new method or tool and everything is thoroughly explained, definitely worth checking!


Towards Data Science is an amazing blog where thousands of independent authors share their knowledge and expertise to expand our understanding of data science. The posts include all skill levels, from beginner to expert, and a broad range of topics including Python, machine learning and statistics.

Some of my recommended articles are:

Data Science and coding cheatsheets

At posit.co you can find really cool stuff! If you click here you will be able to find cheatsheets for many R and Python packages to make your coding much easier!



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