Artificial Intelligence (AI) is transforming the way we interact with technology, enabling machines to think, learn, and adapt in ways that mimic human intelligence. From intelligent chatbots to autonomous robotics, AI is becoming an essential part of our everyday lives and has the potential to transform entire industries. This unit introduces the core concepts of AI, starting with foundational principles and real-world applications. You will explore key machine learning approaches, including both supervised and unsupervised learning, and examine advanced topics such as reinforcement learning, classical and heuristic search strategies, and deep learning, with a focus on convolutional and recurrent neural networks for tasks like image classification and natural language processing. Additionally, you will examine ethical AI practices, addressing the societal impact of AI and the importance of ensuring fairness, transparency, and accountability in AI systems. The unit also covers cutting-edge trends like cloud-based AI and AI at the edge, which are shaping the future of AI deployment. Through programming and problem-based assessments, you will gain both theoretical knowledge and practical skills in modern AI technologies.

Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.

Feedback from Student Unit and Teaching Evaluations

Students found it challenging to transition to Python coding, particularly as many of their previous programming experiences were primarily in Java. This made it difficult to engage with the programming language specific content early in the term.

COIT20245 (Introduction to Programming), a core PG unit since Term 1 2024, now teaches Python, providing the necessary background for COIT20277. For students without this background, key Python concepts can be briefly reviewed in the first two weeks of term.

Feedback from Student Unit and Teaching Evaluations

Students expressed a desire for more detailed explanations and practical examples to better understand abstract or complex concepts covered in lectures.

Incorporate additional real-world examples and case studies into weekly lectures and tutorials to enhance conceptual understanding and application. These examples will be used to demonstrate key ideas and support learning outcomes.

Feedback from Student Unit and Teaching Evaluations

Some students noted that feedback on assessments could be more actionable and consistent in terms of clarity and usefulness.

Encourage a coordinated approach among teaching staff to ensure feedback is clear, specific, and consistently aligned with assessment criteria. The teaching team will implement a moderation process for assessment feedback to ensure it is constructive, consistent, and valuable for student learning and improvement.