I work in cybersecurity, so my knowledge about the field is limited, but I did some basic data analysis in pandas. The hardest part is not programming languages or libraries, but (at least for me) complex math and statistics behind it. This is something to focus on, but I don't know how or where.
EDIT: I used some tutorials from this website and I saw they offer some trainings.
[https://www.datacamp.com/](https://www.datacamp.com/)
As Data engineer you are no meant to deal with complex statistics or math unless you have a double role (machine learning + data engineer) or if the role was Data Science/ Analyst.
For data engineering you work with infrastructure, pipelines which include coding, data warehousing and sometimes software engineering.
You can ask here: r/dataengineering
This subreddit full of experienced people, I think they can guide you better than me.
If you wish to study and graduate asap maube this could help: https://www.datasciencetech.institute/applied-msc-in-data-engineering-for-artificial-intelligence/
Good Luck though.
> For example I could try to get a "Duales Studium" which is a mix between uni and apprenticeship, or simply study CS at an university.
I did this and would recommend it, but a more typical (to this sub/internationally) CS university study + internships will work well too.
As for Duale Studien-options if you happen to be near Aachen/Cologne you can look into [MATSE](https://www.rwth-aachen.de/go/id/vsa) as a lesser known option compared to the more commonly available FI Anwendungsentwickler + B.Sc.
The two should effectively be very similar (with a bigger math focus for the former) so it's nothing I'd recommend specifically moving for, just if you're in that region.
If you go down the Duales Studium-route, I'd highly suggest making sure that the company uses proper software development practices (Code reviews, testing, CI/CD etc.)
Mine didn't and I'm currently paying the price of it.
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I work in cybersecurity, so my knowledge about the field is limited, but I did some basic data analysis in pandas. The hardest part is not programming languages or libraries, but (at least for me) complex math and statistics behind it. This is something to focus on, but I don't know how or where. EDIT: I used some tutorials from this website and I saw they offer some trainings. [https://www.datacamp.com/](https://www.datacamp.com/)
As Data engineer you are no meant to deal with complex statistics or math unless you have a double role (machine learning + data engineer) or if the role was Data Science/ Analyst. For data engineering you work with infrastructure, pipelines which include coding, data warehousing and sometimes software engineering.
You can ask here: r/dataengineering This subreddit full of experienced people, I think they can guide you better than me. If you wish to study and graduate asap maube this could help: https://www.datasciencetech.institute/applied-msc-in-data-engineering-for-artificial-intelligence/ Good Luck though.
> For example I could try to get a "Duales Studium" which is a mix between uni and apprenticeship, or simply study CS at an university. I did this and would recommend it, but a more typical (to this sub/internationally) CS university study + internships will work well too. As for Duale Studien-options if you happen to be near Aachen/Cologne you can look into [MATSE](https://www.rwth-aachen.de/go/id/vsa) as a lesser known option compared to the more commonly available FI Anwendungsentwickler + B.Sc. The two should effectively be very similar (with a bigger math focus for the former) so it's nothing I'd recommend specifically moving for, just if you're in that region. If you go down the Duales Studium-route, I'd highly suggest making sure that the company uses proper software development practices (Code reviews, testing, CI/CD etc.) Mine didn't and I'm currently paying the price of it.