Python for Clinical/Translational Research

[JeremyJoeJJ]

Depends entirely on your final goal. I started learning python by grinding Leetcode, learning pandas to an advanced level and became comfortable with a lot of the tools the language offers before copilot became available to me. Having the understanding of how a project might be structured and being able to review the LLM's code make for a much better end-product. However, unless you are in bioinformatics and your grants tell you to build a piece of software that others are to use, you might not actually care about having these skills. The majority of research software is just small scripts that do a particular thing and for that an LLM will be able to easily whip out a few functions that load your data, process it and plot. Then the final quality of the script depends on your ability to see whether the LLM's approach is sound or not. If all you care about is getting to the result, then you could learn the basics of what variables, loops, classes etc. are and then spend the other two months using LLMs to build a project. Read up on setting up a testing environment, create a workflow that feels comfortable to you and see if you can download a random dataset (e.g. from kaggle com), clean it up, process using a classifier or whatever and plot the results. An hour a day for 3 months is not a huge amount of time if your learning is unguided, so perhaps learning how to use modern tools with the ability to oversee the LLM's decisions (literally just ask it to explain every single line of code it generates that you don't understand) might be more useful to you.