
Hardware for machine learning lesson for IB Diploma Computer Science (first assessment 2027), with editable PowerPoint slides, a student worksheet and full answers. Machine learning needs heavy parallel computation, so students look at GPUs, TPUs and cloud hardware and how they speed up training.
Written for the 2027 IB Computer Science guide, unit A4 Machine learning. Everything is editable, so you can adapt it to your class.
What’s included- PowerPoint lesson (10 slides) with speaker notes on every slide
- Student worksheet (Word), ready to print or edit
- Answer sheet (Word) with model answers for every question
By the end of the lesson students can:
- Compare CPUs and GPUs for machine learning work
- Describe TPUs, ASICs, FPGAs and edge devices
- Recommend hardware for a scenario, separating training from inference
Worksheet sections: A. Key words; B. Training and inference; C. Recommend the hardware; D. Exam-style question
Every lesson includes- Learning goals and a starter question
- Clear explanations with worked examples (Python where code is needed)
- A quick check and a “your turn” task linked to the worksheet
- An exit ticket
- PowerPoint (.pptx) and Word (.docx), fully editable
- Works in PowerPoint and Google Slides
- Calm pastel design, consistent across the whole IB course
These are independent resources written for the IB Diploma Programme Computer Science guide (first assessment 2027). They are not produced or endorsed by the International Baccalaureate Organization.
More lessons in this series- Previous lesson: Machine learning approaches – IB Computer Science lesson
- Next lesson: Dimensionality reduction – IB Computer Science lesson
- Save with the bundle: Machine Learning – IB Computer Science (17 lessons)
Last updated: November 2026.
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