Which Should I Focus On: System Design or AI/ML?

Honestly, at this point in your studies, I’d say focus on building projects rather than jumping straight into system design or AI/ML. These topics are often more relevant for mid-senior level roles. Start by gaining a solid understanding of programming and best practices. Once you have some experience, then dive into system design or explore AI/ML based on your interests and the roles you aim for.

Make sure you have a good grip on core Python and its libraries like Pandas, NumPy, and Matplotlib. Then, shift to data structures and algorithms. After mastering those concepts, you can effectively tackle machine learning, deep learning, and eventually deployment.

I recommend starting with system design. Understanding system mechanics—how data flows and how systems operate—will make you adaptable to any changing AI/ML tools. I learned programming over 25 years ago, and the foundational knowledge of how things work has been far more useful than just jumping onto the latest tech trends.

Why not learn both? If you need to pick one, it really depends on your career goals. For system design, especially in distributed systems, you want to know how to structure clean code and understand underlying processes. It's more common to see this in medium to large companies and at mid-senior level roles. AI/ML skills are incredibly valuable for data science roles where you analyze large datasets. However, they do require a strong foundation in subjects like linear algebra, multivariable calculus, and probability to truly grasp the concepts beyond just using tools.

If you're considering AI/ML, check out this roadmap: [AI Learning Roadmap](https://github.com/bishwaghimire/ai-learning-roadmaps). It can really guide you through the important concepts!