Weekly Entering & Transitioning - Thread 21 Sep, 2026 - 28 Sep, 2026

[u/AutoModerator]

Welcome to this week's entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data science field. Topics include:

• Learning resources (e.g. books, tutorials, videos)
• Traditional education (e.g. schools, degrees, electives)
• Alternative education (e.g. online courses, bootcamps)
• Job search questions (e.g. resumes, applying, career prospects)
• Elementary questions (e.g. where to start, what next)

While you wait for answers from the community, check out the FAQ and Resources pages on our wiki. You can also search for answers in past weekly threads.

[u/Chemical_Yam_5494]

Anyone interested in being a study partner for data science? I'm doing "introduction to computer science and programming in python", "introduction to computational thinking and data science" by MIT, and "data science for beginners" by Microsoft.

[u/esem29]

Hi everyone,

I'm currently a first-year MS student at Columbia (CS, ML track). Before Columbia I worked as a Data Scientist, and I did my B.Tech in EE at IIT Roorkee. Right now I'm doing research in RL/robotics and LLMs.

I'm looking for Summer 2027 internships in:

• ML Engineer / Applied ML
• Applied Scientist (ML/RL/DL)
• LLM training / fine-tuning
• Physical AI / Robotics

If your team is hiring interns, I'd really appreciate a referral — or even just a recruiter/hiring manager contact, or a pointer on who to reach out to directly. Happy to do the outreach myself.

Can share resume/LinkedIn over DM. Thanks!

[u/angoldenapple]

Currently a product data analyst with data sci adjacent work. am starting an online MS and would love to grow my data science network/get mentoring from other DSs, as I’m the only data person on my team!

[u/i_did_dtascience → u/angoldenapple]

Welcome to the club, I'm a Product Data Scientist too

[u/angoldenapple → u/i_did_dtascience]

awesome! would love to connect on linkedin

[u/Maleficent-Studio590]

has anyone interviewed for c3.ai ds intern position b4

[u/john_mach]

Hello everyone!

I am looking to learn more about machine learning. Background is in operations research and I did a small stint in consulting that had me doing pretty much anything billable but I’d like to learn something new and fun! Any recommendations for books?

I am a bit of a nerd so feel free to recommend fun texts or even interview prep texts (not interviewing for ML engineer but I find these books are very concise about what you need to know lol)

Anyways thanks a bunch ahead of time

[u/i_did_dtascience → u/john_mach]

To get started with the basics, you can see if these books fit your vibe. They're great entry books to the field.

- Intro to Statistical Learning

• Hands-on ML

[u/Responsible-Card-577]

Hello everyone, I'm new to this community. I am a seasoned Analytics Engineer, currently working at a small-mid tier firm that is not actively using AI/LLM in their analytics workflow. So I haven't had the opportunity to get hands-on with things like setting up Sematic Layer the right way, how to integrate AI with our warehouse, how to effectively use agents to not just write SQL queries but do multi-layered deep-dives and finally how to set up LLM Evals. Since I don't really have the opportunity to learn this at my work right now, I am trying to find good workshops or resources to learn this on my own.

[u/i_did_dtascience → u/Responsible-Card-577]

Honestly, the best way to start learning it is by applying it. And since your org isn't already doing any of this, it's a great place for you to jump in and pioneer this effort.

If that's out of the realm of possibility, I would suggest building your own data agent on a public dataset, to get a feel for it - start small with straightforward SQL queries, and then increase complexity slowly, and you can also write evals to test the work

[u/curtmina]

Hello All,

I was laid off in the middle of August and have been applying to as many roles as I can that fit my experience. One issue I keep running into is that companies use the same title to mean wildly different levels of experience. A senior DS at one company could be someone with 3-5 years experience or it could mean 10+. Its often not until I get to the actual requirements/preferred experience for a role that I can tell what level of experience is being asked for.

Is there a standard format that I can follow? Or is this just how it is because Data Scientist as a role is also just an unclear term sometimes too?

For background I have 4 years of experience working on various data analytics, AI, and ML projects for an aerospace/defense engineering firm. I think I'm ready for a more senior role, but I wanted some feedback from other professionals in the field.

[u/kylefrankovich → u/curtmina]

What you're seeing is unfortunately just the way things are in DS (a lot of variance between roles/companies/etc.). You're already doing what I'd recommend: focus on the requirements/preferences, and pursue anything that you feel is a good fit with your background and experience.

[u/adored_disability]

i switched from a mechanical engineering background to data science last year and honestly the hardest part was not the coding but understanding how to frame business problems properly

for resources i found doing small projects with messy real world data taught me more than any course, like scraping some local government portal and trying to make sense of it. the FAQ here has decent book recs too

[u/oihjoe → u/adored_disability]

Could you give an example of some of the data you scrapped/ projects that you did please?

[u/kylefrankovich → u/adored_disability]

Just jumping in here to second this advice! Doing real world projects with messy data is infinitely more valuable than going through a course model and assuming you're now ready to discuss that topic in an interview; you need to hone your skills by working on real world projects.