MACHINE LEARNING

What this module is about

Module Introduction

This module provides a hands-on approach to machine learning, focusing on real-world data analytics applications. It begins with fundamental mathematical concepts and gradually introduces a range of learning models, paradigms, and algorithms. Emphasis is placed on both theoretical understanding and practical implementation using software tools. The module culminates in designing a comprehensive application system that integrates multiple machine learning components. Additionally, it covers state-of-the-art models and recent advancements in model deployment, ensuring a systematic approach to machine learning implementation.

Key learning objectives

1. Articulate the legal, social, ethical, and professional issues faced by machine learning professionals.
2. Understand the applicability and challenges associated with different datasets for the use of machine learning algorithms.
3. Apply and critically appraise machine learning techniques to real-world problems, particularly where technical risk and uncertainty is involved.
4. Systematically develop and implement the skills required to be effective member of a development team in a virtual professional environment, adopting real-life perspectives on team roles and organisation.