The Almost Astrophysicist

After working as a data scientist at Uber and now Stripe, I’ve seen what’s useful, what’s noise, and how to build the kind of foundation that actually lasts. Whether you're just starting out or trying to reconnect with the basics — I hope this helps you find your version of the path 🚀 

If I had to start learning data science all over again in 2025… this would be my exact roadmap 🧭 From Python and SQL to machine learning, statistics, and actually understanding what matters in a real tech job — this is how I’d approach learning data science today (without getting lost in 12 course tabs and a sea of contradictory advice 😅)

Wherever you are in your journey, you’re not behind — you’re just getting started ✨

🕒 Timestamps
00:00 a full roadmap outline
02:39 SQL + solving problems!
07:02 python + example
09:44 ML info + project ideas + random regression explanation
14:22 math math math
16:31 stats basics
18:41 business acumen

🔗 Links
1. https://datalemur.com/questions/laptop-mobile-viewership
2. https://datalemur.com/questions/repeated-payments
3. https://www.classes.cs.uchicago.edu/archive/2024/
4. deep learning pdf: https://udlbook.github.io/udlbook/

🧠 Keywords: learn data science, data science 2025, data science roadmap, how to become a data scientist, data science from scratch, SQL for beginners, python for data science, machine learning for beginners, no CS degree, data science career path

👉 Subscribe if you’re into real, unfiltered data science content. And leave a comment if anything hits — would love to hear your story too.

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Welcome to The Almost Astrophysicist — I’m Priya, a data scientist sharing real, unfiltered stories about navigating tech 💻, burnout 🧠, career growth 📈, and (mostly) just learning out loud. From physics undergrad to startups, Uber, and Stripe, I’ve picked up a lot (and maybe made a lot of mistakes too 😅). This channel is where I break down what it’s actually like to work in tech, reflect on the messy parts of ambition, and talk through both the qualitative and quantitative sides of building a meaningful career. Expect technical data science content, chat about what it's like working at high-growth companies, dealing with imposter syndrome, and figuring out what “success” even means.

Subscribe if you’re into data science that feels a little more human 🤍 — and comment anytime, I’d love to hear your story too!!

LinkedIn: https://www.linkedin.com/in/priya-l-520311145/

how I'd learn data science if I had to start over in 2025

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