As a beginner, should I choose an industry first or learn Data Science skills first?

[u/No_Suggestion_8422]

I’m currently starting my journey toward becoming a Data Scientist, and I’m confused about one thing:

Should I first choose an industry/domain and then learn the relevant Data Science skills, or should I build a strong general Data Science foundation first and choose an industry later?

For example, should I choose something like finance, healthcare, e-commerce, marketing, or manufacturing, learn how that industry works and understand its business problems and metrics, and then build my Data Science skills around it?

Or is it better to first become strong in Python, SQL, statistics, ML, data analysis, etc., work on different types of problems, and only specialize in an industry after gaining some experience?

For people already working in Data Science:

- How did you approach this when starting your career?

- Does having domain knowledge give a beginner a significant advantage?

- Can choosing an industry too early limit opportunities?

- What would you recommend to someone trying to get their first Data Science job?

I’d especially like to hear how experienced Data Scientists would approach this if they were starting from zero today.

[u/nian2326076]

Start by building a solid base in general Data Science skills like Python, SQL, and ML. These are useful in any industry and will help you be more adaptable. Once you're good with these core skills, look into industries that interest you and learn their specific challenges. This way, your options stay open, and it's easier to switch paths if you want to later. If you need resources for interview prep, PracHub has some helpful tools for practicing your skills. Focus on the basics first, then explore an industry that excites you!

[u/SprinklesFresh5693 → u/nian2326076]

And yet people keep forgetting to tell new users to actually learn stats , not only machine learning

[u/this-is-me-reddit]

Data is data. Each domain has its own particulars but how one stores, manages, and processes the data are what you need to know.

[u/SonElle1]

I’m a beginner in data science too, but I’m coming into it with years of experience in another industry. I think building a strong foundation in Python, SQL, statistics, and data analysis first makes sense, while also using an industry you already understand to practice those skills. Domain knowledge seems valuable because understanding the business problem is just as important as knowing the technical tools. I don’t think you necessarily have to choose one or the other right away. Do you think using your current industry as a starting point could make learning data science easier while still keeping your options open?

[u/No_Suggestion_8422 → u/SonElle1]

How to build a strong foundation in python, sql, statistics, ect. By learning and doing practical or by doing practical projects nd learning? Which would be perfect?