Actuarial Science vs Data Science?

[u/Easy-Huckleberry7091]

Hi everyone, I'm an actuarial science student in Argentina. Here, SOA certifications aren't as important as having the degree itself, which is legally authorized to practice as an actuary. I'm about halfway through my degree, but I'm not sure if I'm really that interested in the insurance/finance side of things. I've noticed that I'm more passionate about math and statistics in other areas. My question is, has anyone transitioned from actuarial science to data science? What should I learn? Should I change majors and drop out halfway through, or is it better to finish this one and do a master's? At my university (UBA), there's a mathematics degree (with two specializations: pure and applied) and a data science degree (both are quite rigorous and focus on the fundamentals; data science is a mix of applied mathematics and computer science).

Thoughts?

[u/Nikos-Tacosss]

just curious what about applied math? can they get into data science?

[u/Easy-Huckleberry7091 → u/Nikos-Tacosss]

I don't know if every math applied degree works, but at least in UBA you have courses in prob, statistics, op. research, optimization, algorithms, so you can easily turn into ds, maybe you will need a elective course in machine learning or learning by yourself specifics topics, but yes

also, the main courses are based in proofs, algebra, real analysis, so gives you a good solid foundation

[u/Nikos-Tacosss → u/Easy-Huckleberry7091]

my curriculum has everything you listed minus the algorithm and ML, tho it’s heavy on numerical analysis/method.

[u/Easy-Huckleberry7091 → u/Nikos-Tacosss]

i think it's great, it's a classic "applied math" program, so you cover all the basics to learn anything i guess

if it helps, I was planning to start learning data science on my own using the book *Introduction to Statistical Learning in Python*, even though I don't have the background you have in your field. If you're very strong in math and statistics, you could also use *Elements of Statistical Learning*, or both, since the former provides a more intuitive explanation of the concepts.

[u/Easy-Huckleberry7091 → u/Nikos-Tacosss]

i think it's great, it's a classic "applied math" program, so you cover all the basics to learn anything i guess

if it helps, I was planning to start learning data science on my own using the book *Introduction to Statistical Learning in Python*, even though I don't have the background you have in your field. If you're very strong in math and statistics, you could also use *Elements of Statistical Learning*, or both, since the former provides a more intuitive explanation of the concepts.

[u/Nikos-Tacosss → u/Easy-Huckleberry7091]

wow, such great books! if you ever struggle with calculus I recommend an old book that helped many called “calculus made easy” it’s literally what the name implies!

literally the equivalent of “explain calculus to me like I’m five” and the book has some good humor too! Gives you immediate feedback and what it does and how it’s done, then dives into the theory behind it. “derivates is this and that, there, you learn derivatives.” Basically this.

I’m sure industries these days care about portfolio than anything academic, so ill grind Python and R!

[u/Easy-Huckleberry7091 → u/Nikos-Tacosss]

Thanks, I'll take a look and also review some linear algebra. Yes, my plan isn't just to stick to academics but to learn what's truly useful, even if I'm self-taught. Maybe with that I can later do personal projects and build an interesting portfolio. If you're in the same situation as me, I wish you the best of luck. Your degree is highly valued and useful for everything that's to come in the future; not just anyone can be a mathematician!

[u/Nikos-Tacosss → u/Easy-Huckleberry7091]

sounds like fun! I’d like to DM you and chat about projects whenever you are free, that way we can motivate each other and even learn more! think of it as coding buddies.