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Recommended devices

To help you succeed in your studies and work independently, we recommend that you have your own device. 

Laptop

We recommend that students have devices that meet the following specifications:

  • Operating System: Windows 11
  • Processor: Intel i5
  • RAM: 16 GB RAM
  • Hard Drive: 256 GB
  • Screen: 13” or greater
  • Internet Connection: Minimum 2Mbps internet connection with either cabled internet / 802.11AC or faster Wi-Fi.
  • Web camera and microphone: Yes.

 

For Chromebook and MacBook users: We highly recommend Windows 11 laptops for your studies, because some of the Apps you’ll need only work on Windows OS.

Having a device that meets these specifications will enable you to work independently on assigned tasks.

 

Specifications for Master of AI Integrated IT Solutions and Postgraduate Diploma in AI Integrated IT Solutions

All students are required to bring their own laptop to participate fully in coursework, labs, and projects. The following minimum specifications are required:

Processor (CPU):

  • Intel Core i7 (12th gen or later) OR AMD Ryzen 7 (5000 series or later)
  • Apple Silicon (M1/M2/M3) devices also supported

Memory (RAM):

  • Minimum: 16 GB
  • Recommended: 32 GB for data-intensive and AI-related tasks

Storage:

  • Minimum: 512 GB SSD
  • Recommended: 1 TB SSD
    (Students will also receive cloud storage via institutional accounts.)

Graphics (GPU):

  • Dedicated GPU strongly recommended for AI, ML, gaming, or simulation courses:
    • NVIDIA RTX 3060 or above, OR Apple M1/M2/M3 Pro/Max equivalent
  • Integrated graphics acceptable for coursework-only students, but may limit performance in electives such as Game Development or Deep Learning

Operating System:

  • Windows 11 (preferred), OR
  • macOS Ventura or later, OR
  • Linux (Ubuntu 22.04 or equivalent)

Connectivity:

  • Wi-Fi 6 (802.11ax) or later
  • Minimum 2 × USB-A/USB-C ports, HDMI (or adapter)
  • Headset with microphone for online sessions

Other Requirements:

  • Webcam (built-in or external) for online classes
  • Ability to run virtualisation / containers (e.g., Docker, VMware, VirtualBox)
  • Access to cloud services (AWS, Azure, GCP – provided via student accounts)

Notes for Students

  • High-end GPUs are particularly recommended if you plan to take courses in Game Development, Data Mining, or Advanced Machine Learning.
  • The institution provides access to specialist labs, cloud environments, and licensed software for workloads beyond BYOD capacity.
  • Chromebooks, iPads, and tablets are not suitable as a primary device.