Laptop requirements for data and AI courses, by programme

Requirements by programme

The table below is our working guidance, not a vendor specification. Where a vendor publishes a hard minimum, it is linked.

Two facts from Microsoft's Power BI Desktop requirements page catch people out. It needs Windows 10 or later, so there is no macOS version. And it requires a display of at least 1440×900 or 1600×900; a lower resolution such as 1366×768 falls below that floor because some dialogs draw off-screen. Microsoft lists at least 2 GB of RAM available with 4 GB or more recommended, which is a floor for Power BI alone, not for Power BI plus a browser plus a live class.

Check the machine you already own

Before buying anything, find out what you have. This script uses only the Python standard library and runs on Windows, macOS and Linux:

import os
import platform
import shutil
import struct

bits = struct.calcsize("P") * 8
disk = shutil.disk_usage(os.path.abspath(os.sep))
free_gb = disk.free / 1024**3

print(f"Operating system : {platform.system()} {platform.release()}")
print(f"Python build     : {bits}-bit")
print(f"Logical CPUs     : {os.cpu_count()}")
print(f"Free disk space  : {free_gb:.1f} GB")

checks = {
    "64-bit Python": bits == 64,
    "At least 4 logical CPUs": (os.cpu_count() or 0) >= 4,
    "At least 50 GB free": free_gb >= 50,
}
for name, ok in checks.items():
    print(f"{'OK  ' if ok else 'LOW '} {name}")

RAM is not portable to read from the standard library, so check it by hand: on Windows, Task Manager → Performance → Memory; on a Mac, Apple menu → About This Mac. Screen resolution is under Display settings.

Decision rules for buying or upgrading

Work through these in order and stop at the first one that applies.

1. 1Your laptop has 8 GB, an SSD and a 64-bit OS. Keep it. Clear 50 GB of space and start.
2. 2It has 4 GB of RAM. Check whether the RAM is upgradeable (search the exact model number). Adding a stick is far cheaper than a new laptop. If it is soldered, cloud notebooks cover the Python parts of DS and GenAI, but a Power BI-heavy DA course will struggle.
3. 3It has a hard disk (HDD), not an SSD. This, more than the processor, is why old laptops feel slow. An SSD swap is often the best single upgrade.
4. 4You are on a Mac and choosing the DA programme. Plan for a Windows environment before the Power BI module, or ask the institute how Mac users complete it.
5. 5You are choosing an FDE track and have 8 GB. You can start; the first months are Python and SQL. Upgrade before the containers and deployment phase if the machine struggles.
6. 6You need to buy. Prioritise in this order: 16 GB RAM, SSD of 512 GB, a 1920×1080 screen, then the processor. A dedicated GPU is last.

Where cloud notebooks fill the gap

Free hosted notebooks such as Google Colab and Kaggle Notebooks run Python in the browser, and both have offered limited free GPU time; check each provider's current quota because it changes. They are useful for deep-learning exercises, for trying code on a weak machine and for sharing a runnable notebook with a mentor. They are not a full substitute: sessions time out, files need re-uploading, and you cannot run Power BI Desktop or Docker in them.

The parts people forget

• A second screen. During a live class, one screen for the session and one for your own editor saves more frustration than extra RAM. An old monitor or a TV with HDMI works.
• Headset with a microphone. You will ask questions aloud and present projects.
• Stable internet. A live session needs a consistent connection; keep a mobile hotspot as backup.
• Admin rights. Office laptops often block installing Python, Git or Docker. Do not plan to study on an employer's machine without checking policy.

If you are unsure which track you are buying for, compare the Data Science and Data Analyst programmes first — the operating-system question is the one that differs most between them. The FDE for Freshers page lists the engineering tools you would install later in that track.