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Jobs/career advice needed for IT/Computer science

Hello everyone,

I did my studies and finished my master's in natural sciences, only to find out that the ground is too shaky and jobs/prospects are scarce. Also, after long term unemployment, although I enjoy my studies, I lost a bit my interest in academic work. Since I have a second degree in business administration, I would like to know which (easy) IT/computer science skills could I possibly learn for home-based/flexible, stable and international (can be done it different countries, resilient to moving abroad etc.) opportunities in all areas but especially in finance, as it is somewhat related to business administration. I am also open to ideas for 2-year degree options. I would really appreciate your feedback. Also, I do not like routine work so much, so I would prefer areas and skills offering room for self-development, diversity etc. Keep in mind that I would be a complete beginner (or stranger to be honest) in IT/computer science and I don't have any skills at the moment. Feel free to recommend also other forums - websites if you think I could find helpful advice there.

Have a nice day and thanks in advance.
Reply 1
With an aptitude for natural sciences, you might find learning R to be a good stepping stone into the world of data science. This could offer a valuable pathway into further education in terms of data science and analysis, and the opportunity to branch back into science if you rediscover a passion for it, whilst opening another door for learning more programming languages or even exploring data science further with more technical concepts.

R isn’t too hard to grasp and there are plenty of free and paid courses available online with a quick google search! It’s also a great way of showing technical aptitude to employers by being savvy with a programming language AND data manipulation all in one. My boyfriend studies a humanity and has found branching into R to be easy but also with enough challenge available for stimulating him into trying more areas of data science. Hope this helps!

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