I'll be studying data science this semester and need a Windows laptop. My budget is $2,000–$2,400, and I'd prefer an Intel processor, a 15-inch display, an SSD, and 1–1.5 kg of weight. What specifications should I prioritize, and are there any features I should avoid or look for?
4 Answers
I’d avoid a touchscreen if you don’t specifically need one. It can add weight and become annoying during normal laptop use. Also look for a comfortable keyboard with backlighting, since you’ll probably spend a lot of time writing code and working with notebooks.
The 1–1.5 kg limit may be the hardest requirement to combine with a 15-inch screen and powerful hardware. High-performance processors, extra cooling, and dedicated graphics usually make laptops heavier. If portability is more important than maximum performance, prioritize 32 GB of RAM, a good Intel CPU, a reliable SSD, and strong battery life over a dedicated GPU.
Since Windows is a requirement, focus on a model with a strong recent Intel processor, plenty of RAM, and fast SSD storage. For data science work, 16 GB of RAM should be considered the minimum, while 32 GB would give you more room for larger datasets and virtual environments. A dedicated GPU is useful for some machine-learning workloads, but it may make the laptop heavier and reduce battery life.
Windows is perfectly workable if you need compatibility with a particular program. Some developers prefer macOS or Linux, but the operating system should be based on the software your classes require. It may be worth checking course requirements before choosing hardware.
That’s my concern too—if a required application only supports Windows, switching platforms could create unnecessary problems.
Backlit keys are worth checking in person or in detailed reviews. Some people love them, while others turn the lighting off, so it mainly comes down to personal preference.