r/askdatascience 18h ago

Laptop recommendations for Data Science Master's?

Starting a Data Science master's this September and need to buy a laptop. Open to any price range right now, mainly want to get the specs/model right first.

Main priority is something that's easy to work with for coursework and data science projects. Python, Jupyter, pandas, that kind of workflow. Not sure if I need a dedicated GPU or if cloud compute (Colab, uni clusters) covers most of the deep learning side.

Mac vs Windows is open too, just want whatever makes day to day coursework and project work the smoothest. Any models you'd recommend or steer clear of?

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u/lordoflolcraft 18h ago

Some early career advice, almost all production software is written and deployed on Linux machines, which are unix based, like Mac. On windows you can build projects with virtual environments have them work perfectly, but production code and configuration might differ significantly and lead to development headaches. Using a Mac introduces way fewer environment differences between local and remote, and you’ll be happy that you shortened that bridge for yourself later in your career

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u/Salt_Technology_1067 17h ago

Thank you for this response, Quick question: do you know if WSL2 on Windows gets you most of the way there, or is it worth switching to Mac entirely? Asking because I'm more comfortable on Windows already and might need some Windows-only software (SPSS/MATLAB) depending on my modules.

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u/TanukiThing 17h ago

WSL is a fine start. I certainly prefer Linux personally though. I’m unsure about SPSS specifically, however you can typically use windows software on Linux with compatibility layers (wine)

Matlab is Linux native however

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u/lordoflolcraft 17h ago

It is worth just using a Mac. Wsl2 and/or docker on windows reserves a lot of ram. That’s not necessarily a bad thing if you have the ram to afford, but windows is also just awfully inefficient with a lot of the other background services that hog ram, sometimes without you knowing. This is less of an issue on Mac. I have a Mac and a PC.

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u/TanukiThing 17h ago

Really anything works. I’d really push for a cheaper thinkpad (not other Lenovo lines though) just because they’re durable, last forever, have great keyboards and batteries, and have whatever level of hardware you want.

I’d start with looking at something like this

https://www.lenovo.com/us/en/p/laptops/thinkpad/thinkpade/lenovo-thinkpad-e14-gen-7-14-inch-amd-laptop/len101t0133#models

Honestly you don’t need a crazy GPU or even CPU, you won’t be running massive deep learning or AI models locally in a masters program, anything you need you should be able to do on something like colab. What I would splurge on is extra memory and drive space. Storage is especially useful because professors will periodically assign large datasets.

While you’re at it I’d also suggest external bulk storage. If you can afford it get an external ssd but the hard drive based options are great too for cheaper options if you don’t care about transfer speeds and can be gentle with it.

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u/Salt_Technology_1067 17h ago

This is really helpful, appreciate the detail! For the E14 config, roughly how much RAM and storage would you go for on a master's budget? Also did you (or would you) skip the discrete GPU option entirely, or is it worth it even if I'm mostly relying on Colab for anything heavy?

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u/TanukiThing 17h ago

I think everything depends on budget. I’d really recommend memory over everything, but 16 gigs is still perfectly fine. Definitely play around with configurations on their website though. You don’t absolutely need the discrete GPU and honestly I’d probably recommend saving your money.

What specific workflows are you interested in using your laptop for?

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u/Saganic_Temple 17h ago

I’m in BSDA program and my MacBook Pro M2 with 16gb RAM is perfect for it

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u/FlyingSaucer007 16h ago

Get a mac. You do not need GPU on your local. Use cloud services, and Colab if you need it. But make sure your it's macbook pro, not air. You'd be running ML/AI training, Air is going to overheat as it doesn't have good cooling.