Course overview
Statistical Machine Learning focuses on algorithms that automatically improve their performance through learning. Examples include computer programs that learn to detect objects in images or videos, predict stock market trends, or rank web pages. This advanced course provides a comprehensive overview of key concepts, widely used techniques, and foundational algorithms in statistical machine learning. It covers core topics such as dimensionality reduction, classification and regression, support vector machines, and deep neural networks, as well as recent developments including Large Language Models (LLMs), Agentic AI, and Causal AI. The course is designed to equip students with both the theoretical foundations, practical skills and intuition behind modern statistical machine learning methods. By the end, students will have a solid understanding of how, why, and when to apply these methods to real-world problems.
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The Student Contribution amount displayed below is for students commencing a new program from 2021 onwards. If you are continuing in a program you commenced prior to 1 January 2021, or are commencing an Honours degree relating to an undergraduate degree you commenced prior to 1 January 2021, you may be charged a different Student Contribution amount from the amount displayed below. Please check the Student Contribution bands for continuing students here. If you are an international student, or a domestic student studying in a full fee paying place, and are continuing study that you commenced in 2025 or earlier, your fees will be available here before enrolments open for 2026.