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Listed under:  Mathematics  >  Statistics and probability  >  Distributions (Statistics)  >  Data types
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Computer Science Fundamentals

This curriculum provides a teacher guidebook for implementing lessons, with learning and teaching activities, content, printable worksheets and some assessment lessons.

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How can AI recognise what it sees?

This lesson is an introduction to the way in which a computer sees. It focuses on image recognition that involves feature extraction, object detection and classification. This lesson was developed in collaboration with Dr Karsten Schulz, Digital Technologies Institute.

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Visual to text coding: Lesson 2

This is the second in a series of lessons to transition from visual coding to text-based coding with a general-purpose programming language. This lesson may take two to three 45-minute periods. It introduces how to make decisions (branching) and identify data types.

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Data bias in AI

Artificial intelligence can sometimes be biased to certain shapes or colours. When such AI systems are applied to situations that involve people, then this bias can manifest itself as bias against skin colour or gender. This lesson explores bias in AI, where it comes from and what can be done to prevent it.

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Fun projects with language translation

Natural language processing is growing in importance. We often converse with automatic chatbots for customer service without even knowing. We also use online translation services or mobile apps. But how do these services work? Is there artificial intelligence (AI) in them? Three projects are offered to cater for student ...

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Recognising AI

Use the tasks in this lesson to introduce concepts that underpin artificial intelligence (AI). The majority of the tasks are unplugged (do not require a digital device). Use the downloadable AI cards with your students to explore what they know about AI.