What Windows laptop should I buy for data science on a $2,000–$2,400 budget?

Since you specifically need Windows, look for a standard clamshell laptop rather than a 2-in-1 touchscreen model. A non-touch display usually saves weight, improves battery life, and avoids accidental inputs. A 15-inch screen with a comfortable keyboard, good cooling, and a bright matte panel will be more useful for long programming sessions than extra cosmetic features.

For data science, prioritize 16–32 GB of RAM, at least a 1 TB SSD, and a recent Intel Core i7 or Core Ultra 7 processor. If you’ll work with machine learning locally, a dedicated NVIDIA GPU with at least 6 GB of VRAM can help, although many courses rely on cloud notebooks instead. Your 1–1.5 kg weight limit may be difficult to combine with a powerful GPU, so decide whether portability or graphics performance matters more.

A backlit keyboard is worth checking for, especially if you’ll be studying or coding at night. I’d also verify that the RAM and SSD are large enough before buying, because some thin laptops have soldered memory and limited upgrade options. Aim for 32 GB of RAM if your budget allows; it gives you more room for virtual environments, notebooks, databases, and browser tabs.

Keep in mind that a thin 15-inch Windows laptop under 1.5 kg may use integrated graphics and have limited cooling. That’s perfectly fine for Python, SQL, statistics, and most coursework, especially if you use cloud-based GPU services. If you expect to train models locally, consider accepting a heavier laptop or using an external monitor and remote computing instead.