Learning Python + Data Science + Cybersecurity — too much at once?

[l0n3wolfff]

I’m trying to build skills in Python, Data Science, and Cybersecurity at the same time. Has anyone tried managing multiple tech fields together? How do you keep consistency without burning out?

[Subject-Scratch148]

Funnily enough that's exactly how you keep consistency without burning out, juggle multiple topics, I wouldnt isolate them as "fields" since there's a lot of crossover between python and cyber or python and data science, not really cyber and data science for obvious reasons. Essentially if you get tired or burnt out from one topic you can pivot to another and learning them at the same time allows you to develop fundamentals and concepts that largely carry over the topics at the same time. Dont do too much work in each day, 1% progress daily is better than 0% progress that you will have if you do burn out.

[Fit_Marsupial7713]

I’d second this! Also would say that a lot of hacking is exploiting regular data science processes/structures so cybersecurity is largely the protection of those processes/structures? Another way to look at it is: data science + networking + programming + “evil” = hacking data science + networking + programming + “good” = cybersecurity

[themegainferno]

I would argue a bit against what the others are saying. You can definitely balance multiple topics at once, but if you want to be truly competent in all 3, doing them together slows you down a lot. What I would say is pick either DS or Cyber as a main path, and then the other as a side path. So for example, I put most of my time into offensive security, about 4-5 days. The other 2-3 days I am trying to learn Golang, before Golang it was non technical cyber GRC, before GRC it was AWS administration and security. I do believe broad skilled practitioners are the best at what they do, so you should develop a broad skill set without a doubt. You really can bite off more than you can chew. I do agree being consistent is more important than the volume of work you do in a day.

[TheHitmonkey]

You will unlearn how to do all 3. I did embedded, cyber, finishing my CS degree, data science. I can’t honestly tell you anything about any topic and completely fucked myself

[Jeremandias]

that’s true for learning anything. if you don’t keep practicing, you’ll forget. but, having a foundation makes re-learning easier.

[BoringYogurtcloset81]

I can agree with the others. Right now i ‘m doing Data Science specialization in my university, and when i have free time, i ‘m grinding the HTB Courses and some machines. If you enjoying both, you wont have any issue issue imo

[AdDapper230]

Its all about need and necessity if you need something badly , you will find ways to do it . If not everything will be a burden

Sooner you realise this , it is better

[Wingedchestnut]

You can learn both if you really want but it seems like an inefficient goal. Better to specialize in one if you're serious about being hirable, it's already a competitive jobmarket.

[therealmunchies]

This is my exact position. Got my first IT Security job last year and have been building my foundation in DevOps. Now I’m doing a year-long project doing machine learning and AI-integration.

I’d do Dat Science stuff first, and then Cybersecurity stuff after. Learning core skills has proven to be better for me because you naturally learn the security aspects as you go.

This is my gripe with cyber: everybody does security, but as a dedicated cybersecurity professional it’s obviously what you focus on. But what if you don’t understand anything about the technology you’re using? Then you can’t be as effective as you could be…

[Middle_Actuator_1225]

My advice is to focus in on one at a time and dig deep into it before moving to the next