Nov 26, 2024
I was never at the top in maths, but I wasn’t bad either and always liked it somehow. At the same time, I thought for a long time: if you’re not great at maths, you can’t go into computer science, data analysis, data science or IT. After a few detours via psychology, I finally ended up in a Salesforce consultant role and successfully completed my degree in business informatics and AI, specializing in software architecture and design, with top marks.
But whether I’m programming with Python, creating machine learning models or analyzing data, I come across mathematical concepts all the time. When using data analysis, automation or Python programming, I don’t think it’s important to understand maths topics in every detail. But mathematical understanding does come up very often. A few months ago, I wanted to brush up on my understanding of maths and logic and came across the app ‘Brilliant’ (no affiliate link). The app explains topics such as probability and regression models in a super simple way. The cool thing about it is that the app is structured similarly to Duolingo and is almost somewhat addictive thanks to the gamification… Read to the end of the article to see how many streaks I have already completed 💪
In this article, I will introduce you to some of the most important mathematical topics that are essential for applied data analysis. If you have beginner or intermediate knowledge and want to deepen your understanding of key…
