If you are looking for a side project, then I recommend working through some tutorials that teach the skills you want to learn. If you are interested in remote sensing, maybe a good first step would be to learn to preform land classification using predictive models.
There are two components to do this. One is learning how to run and write the code to do this, and the other is learning how the models work. Personally, when I am learning I like to get the code running first then learn about the models. That way I have something tangible to play with while I learn.
Here is a good tutorial that I did when I was learning land classification in R.
https://valentinitnelav.github.io/satellite-image-classification-r/
I highly highly recommend working though this, then applying what you learned to the system of your choosing. Interested in grassland ecology? Find a study area, pull satellite imagery of it and classify bushes, rivers, and grass. Simple, but an really useful skill.
For learning predictive models you can go really really deep or just keep it light and get an idea for how the models work. Depends on what your focus is. There are a number of resources out there for learning ML/predictive models. I will point you to section 4.2 of this paper https://www.tandfonline.com/doi/full/10.1080/15481603.2019.1650447 which covers some of the common ones used in land classification that might be of interest to you, and can serve as a jumping off point for you.
On another note many of the quantitative ecologists in my department swear on this book:
https://www.amazon.com/Ecological-Models-Data-Benjamin-Bolker/dp/0691125228
I have not read it so cannot personally vouch for it, but many masters and phd students I know have worked through it at some point.
I currently work as a junior researcher in an environmental data science lab. I love it and I am happy to answer any questions you might have about working in this space.
Happy coding!
I'm not an ecologist, so take this for what it's worth, but perhaps Ben Bolker's book would be a good place to start.
His website: https://ms.mcmaster.ca/~bolker/
Ecological Models and Data in R
https://www.amazon.com/Ecological-Models-Data-Benjamin-Bolker/dp/0691125228
Online PDF for free: https://ms.mcmaster.ca/~bolker/emdbook/book.pdf
Ben Bolker's book is in my opinion a necessary work-through for all ecologists. Models and R code are so clear and well-described, I still use it as a daily resource.