- knitr, as I got sick of LaTeX (I always ended up fiddling with the figure placement forever until it was just right). I also moved all my R work into RStudio, which is a HUGE time saver and the Projects function has saved me a few times.

- snakemake, for reproducible bioinformatics workflows, integrates nicely with HPC systems, and is very beautiful (the few times I've used it)

- I went through the first fast.ai course, and used it with some success on kaggle, but I'm far from doing 'bleeding edge' stuff I think (applied is fine though! give me a nice dataset and I should be fine). I've also read the Kaggle book (Deep Learning with Python), which contains a whole bunch of these weird useful machine learning tips that no-one really can't explain mathematically

- I've also made an effort to switch my R code to immediately use as much tidyverse as possible, which isn't always OK when using bioconductor at the same time