Hey Computer Scientists!
I’m currently interested about the intersection of computer science and biology, specifically in the realms of environmental biology, zoology, and entomology. I have a background in these areas, fyi.
I’m reaching out to you to see if anyone can recommend some great courses (possibly beginner friendly) that delve into the application of computer science in these fields. Whether it’s data analysis, modeling, or bioinformatics, I would like to learn how and what computational tools can be utilized in these fields of biology.
If you’ve taken a course that covers these topics, or if you’ve heard of reputable institutions or online platforms offering such courses, please share your insights! I think that personal experiences and recommendations hold so much value.
Also, if you have any advice on some great books about computer science and biology (that maybe helped you to learn to work in this field), I’d love to hear about it.
Looking forward to your suggestions!
I don’t think I can answer your exact question, but likely you’d want to learn Matlab and Python because of how frequently they’re used to analyze and process data in the research sciences. My daughter is in a geophysics PhD program and pretty much lives in those two.
I have been in software for a loooong time but I have no real background in this field at all. Take what I say with a grain of salt and someone please correct me if I’m wrong.
My wife is finishing her last year of a biology undergrad and thinking to go into data analytics/science. The general sense that I’m getting from the coursera courses and data science books she has been reading has been that, basically, any data science resource would be good enough. Having the foundational knowledge for whatever your field is helps but really it doesn’t seem to matter that much when you get down to it… Finance, animal populations, etc… It’s all numbers and you’re just counting different things at the end of the day.
Things to learn (possibly in order of importance) seem to be…
Either R or Python.
If you’re going with R, you should work with libraries like shiny, ggplot2, and tidyverse.
If Python, check out pandas and numpy.
Git.
Some version of SQL (SQLite is a good starting point).
Excel (but Google Sheets is good enough to start with).
The thing I tend to do when learning a language is to go through a quick and dirty intro book. I really like the “Learn X the hard way” style books… The python one is great. I finish (maybe) 50% of whatever book I’m using and then I move on. I find a project to work on using that language as soon as possible. You’re going to learn more doing this than you will reading a book.
Remember, you don’t need to be an expert… Get the gist and start playing around. You’ll figure out the hard stuff when you get to a problem that requires it. A solid 80% of writing code is just googling for how to do stuff you either forgot or never learned in the first place.
Do NOT spend 8 hours watching “Everything you need to learn python” videos. You will never learn anything doing that.
Books like Learn Python The Hard Way give you a breakdown of the basic tools you have in your toolbox… Strings, integers, lists, dictionaries, variables, etc. The way you solve a problem with code is by combining those tools. Start by combining two of them. Then three. Then five. Then ten. Once you get that flow in your head, you can solve damn near any problem and pick up new languages really quickly.
I appreciate your exhaustive answer. Thanks a lot! I found a lot of useful information. Since I am already learning Python, I believe I will look into your book suggestion and also start looking more into the other topics you covered, such as Git, SQL, and getting better at Excel.
Again, I really appreciate your answer!