AI and Intelligent Systems

Artificial intelligence concepts and systems that process information, identify patterns and support intelligent applications.

Overview

AI and Intelligent Systems introduces how machines can process information, recognize patterns, make predictions and support decisions. Learning starts with clear concepts and practical experiments, and can extend to machine learning, computer vision and AI-enabled applications. Advanced topics are introduced where they are relevant and appropriate; they are not presented as standard offerings in every engagement.

Why It Matters

AI is increasingly present in the tools learners already use. Understanding how these systems work, what they can do and where they fall short is part of being technically literate today.

Core Concepts and Skills

The ideas learners work with in this area, and the practical abilities they develop by using them.

Key Concepts

Rule-based systems versus learned systemsData, features and labelsTraining, validation and predictionClassification and pattern recognitionConfidence scores and error analysisComputer vision fundamentalsNatural language processing basicsLimitations, bias and responsible use

Skills You Can Develop

Framing a problem as a question data could answer
Running and evaluating a simple model with prepared data
Interpreting results, including where a system fails
Adding a responsible intelligent feature to a project
Discussing what AI can and cannot do with clear examples

Representative Learning Pathways

These are examples of subjects and skills within this technology area. Not every pathway is offered in every engagement; scope depends on the learners, timetable and program agreed.

AI fundamentals

What AI is, how intelligent systems are built and where they are used.

Machine learning concepts

How systems learn from examples, and the difference between data, training and prediction.

Computer vision

Image and object recognition, and how cameras can be used as inputs.

AI-enabled applications

Building or using applications that include an intelligent feature.

Data-driven and intelligent automation

Using collected information to automate decisions and actions.

Practical AI experiments

Small, testable experiments that demonstrate an AI idea end to end.

Practical Activities

Exploring AI concepts through worked examples

Running and evaluating practical AI experiments

Training simple models with prepared data

Adding intelligent features to websites or applications

Discussing responsible and appropriate use of AI

Who It Is For

Learners who already use AI tools and want to understand how they work
Educators introducing artificial intelligence responsibly in the classroom
Programs exploring how AI connects to sensing, automation and decision-making

Engagement Opportunities

Introduced through workshops, clubs and project work where the audience and prerequisites are suitable.

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How It Connects

AI connects to Coding through AI-enabled software, to Robotics through perception and autonomous behavior, and to Electronics through sensing systems.

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Whether you are a school, an institution or a learner, we can discuss how this area fits your context and goals.

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