Reddit reviews Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools

Great! Yes, it is true that there is currently a glut of biomedical PhD's in the United States, but I believe computational researchers are in the minority and the pay is still very good. You can Google around for some job stats and career outlook to be certain.

For some basics about what you need in your toolbox, check out http://www.nature.com/nbt/journal/v31/n11/full/nbt.2740.html (computational biology and bioinformatics are routinely used interchangeably). I'd also highly suggest the book Bioinformatics Data Skills which is more like a manual for the skills you need to develop as well as best practices: https://www.amazon.com/Bioinformatics-Data-Skills-Reproducible-Research/dp/1449367372 .

Beyond this, I can't stress the benefits of "on the job" training as a volunteer. Even wet labs (non-computational) could use some help writing scripts to help them build pipelines or analyze their data more efficiently. Seek out professors who you have enjoyed classes with or even scour your University's faculty pages and cold email some people. It's easy to turn away free help from an undergraduate in biology because they need to be trained in all of the assays and they take up precious bench space, but a computational undergraduate could help process data remotely in their underwear at home.

okay, so it looks like you won't need any more machine learning related knowledge then, and most likely you already passed all your algorithms courses too, so you won't need to study that in more detail either. Getting used to the unix command line should be most useful for you at this point then, as DroDro already pointed out - learning to write small bash scripts and using tools like awk, sed etc. might come in very handy later., and maybe you want to look at R in more detail than you did so far too, as that's something that will continue to be useful for years to come.
These are two introductions that most likely contain more details than you need, but might be good for looking things up. regarding Linux: http://www.tldp.org/LDP/intro-linux/html/ and shell scripting, including a short introduction to awk and sed: http://www.tldp.org/LDP/abs/html/
For a more basic introduction to all the necessary computer-related skills, I'd recommend this book https://www.amazon.com/gp/product/1449367372 It explains all the basics you need to know about unix, shell scripts, useful things like git, useful tools, bioinformatics pipelines and contains a short intro to R etc., isn't too over the top and might be good if you're coming from a biology background and aren't too familiar with those yet.

The Bioinformatics Data Skills book is decent to start off after you acquire basic Unix command line skills along with some familiarity with a scripting language (preferably Python).

Generally the Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins is a preferred introductory textbook.

There are lots of online resources. To complement the other ones linked in the comments:

Learn R, in R

Programming: Pick up Python

Programming tools: Adventures with R

I'd start with this for a good general overview that also carries many great recommendations: Bioinformatics Data Skills, by Vince Buffalo.