- 16GB of RAM minimum (32GB is even better.)
- Quad core CPU (Intel i5 or higher, AMD Ryzen 5 or higher, Mac M1/M2)
- 512GB SSD or NVMe for storage. (256GB as an absolute minimum; 1TB is ideal.)
- Thunderbolt 3 or newer. This looks like a USB-C port but allows people to plug in external GPUs (eGPUs). This means that you can use a laptop with an integrated (Intel) GPU day-to-day, connecting to an eGPU when needed for Deep Learning, AI, and Game Development courses.
- If you are looking for brand or model recommendation, please consider:
- Dell XPS 13 or 15
- Lenovo ThinkPad T Series or X1 Series
- Any Apple MacBook[1]
- Microsoft Surface Studio Laptop, Surface Laptop, Surface Book (although only the Surface Studio Laptop includes the aforementioned Thunderbolt port)
- If you are considering a gaming laptop, we recommend an Nvidia GPU, as they are the standard for scientific computing. However, if the machine has Thunderbolt 3, you will be able to sign out an appropriate eGPU when needed.
- Our students will not need to purchase a copy of Matlab, Microsoft Office or development tools, as Queen’s and the School of Computing have licenses that will cover them while they are studying here.
Depending on the budget and needs, if two devices are an option, you may like to have a larger laptop for major development and then something small like a Microsoft Surface, iPad, or Chromebook for taking notes in class. Or a gaming desktop at home that you can use for heavy duty development, and a slimmer laptop for taking back and forth. However, note that an iPad or Chromebook on their own are NOT sufficient for taking most of our courses because you will not be able to install the software you need on them.
[1] Note: Apple’s ARM-based processors (M1, M2, etc) are well-supported, but you may run into issues using it for some tasks (mainly running virtual machines, required by some courses). In these cases, we try to provide accommodations which could require you to come use one of the PCs in our labs.
