Artificial Intelligence

AI encompasses a diverse range of forms and applications. Despite its pervasiveness in our daily lives, we often use AI without realising it. Currently, AI has advanced to the point where it can perform tasks such as driving cars, engaging in conversation, creating written content, producing art, composing music, and even writing computer programs. However, the question remains whether AI will eventually surpass human intelligence and become more human-like. Additionally, the concept of AI achieving sentience raises questions about its potential superiority over humans. Finally, the changing role of robots in society is a topic of debate, as they have evolved from mere tools to potential companions.

What is AI?

The use of AI has both positive and negative impacts on society. On one hand, algorithms used by platforms such as Facebook and YouTube have led some users to consume dangerous conspiracy theories and become radicalised. Additionally, AI-curated content on Instagram has been linked to instances of self-harm among teenage girls. On the other hand, machine-learned suggestions from companies like Google, Netflix, and Spotify can limit users to a limited selection of options, creating an echo chamber. HR software that only selects resumes with specific degrees and skill sets can also perpetuate biases in the hiring process. The increasing use of data in AI highlights its value as a resource, often referred to as the “new oil.”

There are also many positive examples of AI in use today. For instance, email filtering helps to protect users from spam and scams by automatically sorting and blocking unsolicited messages. Autocorrect in word processing software similarly assists users by suggesting and completing words as they type. Chatbots provide a convenient way for online users to communicate and receive quick responses to their questions by mimicking human conversation. These are just a few examples of how AI can enhance and simplify our daily lives.

This educational program is designed to teach advanced students various aspects of Artificial Intelligence and its applications. The curriculum is structured into seven levels, each focusing on a different part of AI. The comprehensive curriculum covers a wide range of topics in Artificial Intelligence and provides students with the skills and knowledge they need to build practical solutions and commercialise their ideas.

How do we use AI in class?

Beginner and Intermediate Courses

Level 1-2

Our Beginner and Intermediate students learn about Mathematics and Logic by applying Computational Thinking principles to programming. Most of the time, they don’t even realise they are studying because, at that level, coding looks like playing. That is their first encounter with Artificial Intelligence. Later, when they join the Advanced class, the students pursue a progressive curriculum designed to prepare them for tertiary studies (University and TAFE).

Level 1

In Level 1, students learn to program robots and drones using programming languages such as Python, JavaScript, Node-RED, and OpenCV. They use these skills to solve complex challenges in various scenarios requiring innovation, adaptability, and teamwork. Additionally, they learn about Project Management and Disaster Resilience by simulating complex missions and war room strategy games.

Advanced Course

Level 2

In Level 2, Advanced students learn Computer Vision with OpenCV and build practical applications such as face tracking, line following, object monitoring, document scanner, OCR, Instagram and Snapchat filters, virtual mouse, virtual painter, money counter, vesture volume control, barcode/QR code scanner, intrusion detection, digital signatures, ArUco markers, etc.

Level 3

In Level 3, the advanced students learn Machine Learning and work on builds such as face recognition, intelligent body monitoring (body poses and gestures), dashboard camera, drowsy driver and lane detection for vehicles, attendance management system, people counting, surveillance and security systems, etc. They will also learn how to use single/multiple linear and polynomial regression to train an AI model to predict data (such as COVID-19), classify waste, recognise faces and others.

Advanced Course

Level 4

In Level 4, the students take the next step to Deep Learning with the PyTorch framework and TensorFlow library. They study neural networks and build projects such as X-rays analyser, obstacle avoidance for cars, AI personal gym trainers, etc.

Level 5

Starting with Level 5, the students learn how to deploy real-world Computer Vision solutions to the web. Nowadays, developers can create fantastic computer vision projects but cannot convert them into commercially viable products they can sell because their apps need attractive graphical interfaces (GUI). Therefore we decided to teach the students web development using HTML, CSS and JavaScript so they can create web apps.

Advanced Course

Level 6

In Level 6, the students will continue to study the principles of good design and user experience to create apps that are not only functional but also user-friendly. They will also learn to use the latest tools and techniques to capture, process, and interpret visual data.

Level 7

In Level 7, the students develop practical solutions they can commercialise, such as clothing virtual measurement tools, retail traffic counters, custom object detection (i.e. suspicious luggage detector or weapons detection), Augmented Reality (AR) virtual glasses try-on, car counters, customer engagement (face emotion), license plate recognition, OCR (text extraction), face mask detector, personal protection equipment (PPE) detection, drowsiness detection, intruder detector, face attendance, blink counter, multiple choice questions (MCQ) automatic grading and more.