1 min readfrom Data Science

Could really use some guidance . I'm a 2nd year Bachelor of Data Science Student

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Navigating the expansive field of data science can be daunting, especially as you approach the midpoint of your degree. With a solid foundation in Python, SQL, and core statistical concepts, you’re well on your way. However, knowing what to focus on next is key to enhancing your skills and career prospects. Should you dive deeper into theoretical concepts, explore new tools, or perhaps tackle advanced machine learning techniques? Seeking guidance from the community can illuminate your path forward and empower your learning journey.

Hey everyone, hoping to get some direction here.

I'm finishing up my second year of a three year Bachelor of Data Science degree. I'm fairly comfortable with Python, SQL, pandas, and the core stats side of things, distributions, hypothesis testing, probability, that kind of stuff. I've done some exploratory analysis and basic visualization + ML modelling as well.

But I genuinely don't know what to focus on next. The field feels massive and I'm not sure what to learn next, should i start learning tools? should I learn more theory? totally confused in this regard

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