Recommended devices
We recommend that students have a device that meets the following specifications to support day-to-day study, coursework and online learning.
Recommended device specifications
| Requirement | Recommended specification |
|---|---|
| Operating system | Windows 11 |
| Processor | Intel i5 |
| Memory | 16 GB RAM |
| Storage | 256 GB |
| Screen | 13 inches or greater |
| Internet connection | Minimum 2 Mbps internet connection using either cabled internet or 802.11ac Wi-Fi or faster |
| Webcam and microphone | Required |
Chromebook and MacBook users: Windows 11 laptops are highly recommended because some applications required for study may only be available on Windows.
Having a device that meets these specifications will help you work independently on assigned tasks.
Specifications for Master of AI Integrated IT Solutions and Postgraduate Diploma in AI Integrated IT Solutions
All students in these programmes are required to bring their own laptop to participate fully in coursework, labs and projects. The following minimum specifications apply.
| Component | Minimum | Recommended / Notes |
|---|---|---|
| Processor | Intel Core i7 (12th gen or later) or AMD Ryzen 7 (5000 series or later) | Apple Silicon M1, M2 or M3 devices are also supported |
| Memory | 16 GB RAM | 32 GB recommended for data-intensive and AI-related tasks |
| Storage | 512 GB SSD | 1 TB SSD recommended. Students will also receive cloud storage through institutional accounts. |
| Graphics | Integrated graphics are acceptable for standard coursework | Dedicated GPU strongly recommended for AI, machine learning, gaming or simulation. NVIDIA RTX 3060 or above, or Apple M1/M2/M3 Pro or Max equivalent. |
| Operating system | Windows 11, macOS Ventura or later, or Linux Ubuntu 22.04 or equivalent | Windows 11 is preferred |
| Connectivity | Wi-Fi 6 (802.11ax) or later | Minimum two USB-A or USB-C ports, HDMI or adapter, and a headset with microphone |
| Other requirements | Webcam and ability to run virtualisation or containers | Docker, VMware or VirtualBox support, plus access to AWS, Azure or GCP through 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 study device.