Should I pursue a career in Spring Boot development or AI/ML?

As a software engineering student, you're focusing on two very different fields. Software engineering is about designing and implementing robust, efficient software, while data science revolves around analyzing data for insights. I’d suggest getting really good at software engineering first—master Java, Kotlin, and Spring Boot. If you eventually want to pivot to data science, a master's in statistics could be a smart move later.

You don’t have to commit to one path just yet! If you enjoy math and research, AI/ML may be more appealing down the line, but backend roles often have clearer entry points. Consider building a solid foundation in backend development with Spring Boot, while also dabbling in ML through side projects or classes. Good software skills will definitely help you transition into ML roles later.

You don’t have to pin yourself down right away! A lot of students explore different areas during their college years. Why not try gaining some hands-on experience in both fields? The one you find more enjoyable will probably stand out to you eventually.

If you love math and research, AI and ML might be the better long-term fit for you. That field typically dives deeper into statistics and experimentation. On the other hand, Spring Boot is about building backend systems. Both paths are fantastic, so it really depends if you see yourself building systems or working with data.

Haha, you spent four days deciding? You could've just flipped a coin! Honestly, why not start with Spring Boot? You'll likely land a job in six months, and if it’s not your thing, you can always switch to ML down the line. At the very least, you'll have a paycheck and some experience.