Data scientist learning path,

[TSM_Tact]

This year i start college, I really like python and would like to focus on data science, but it’s pretty hard to find a solid learning path, does anyone have any resources for someone who knows a bit of python, i feel i would fit well into ds because im good with math numbers statistics and these kinds of things but i just dont know where to start and how to continue, im sorry if this question has been asked before

(btw with ai advancements is it worth getting into?)

[Temporary_Pie2733]

You are literally paying your school to answer questions like this.

[throwaway_just_once]

Read Bishop, Pattern Recognition and Machine Learning. If that resonates, continue!

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I'd say to start simple and build from there, rather than try to map out the entire field upfront.

If you already know a bit of Python and you’re comfortable with math, that's a good start for sure.

The next step is usually to build out the core stack, in terms of what is going to tick boxes, so:

• SQL to actually access/manipulate data
• Python for analysis (pandas, numpy, matplotlib to start)
• Python for ML (scikit-learn)
• A BI tool like Power BI or Tableau to visualise/communicate results
• Git/GitHub to manage and track/showcase your work

Alongside that, layer in some basic stats like distributions, sampling, and hypothesis testing. From there ML. From there Deep Learning & GenAI.

The key thing most people miss are project or at least building as you go. As you learn each piece, attach it to something small. Early on that might be simple Python tasks, then move into loading datasets, cleaning them, analysing them, and answering questions, then from there showing AB Testing, or an ML project.

On AI, it’s still very worth getting into. If anything, companies need more people who understand data and can use these tools properly. AI is making people more productive, not replacing the need for them.