- One Semester or Equivalent
- 48 hours
On-campus unit delivery combines face-to-face and digital learning.
Aims and objectives
This unit aims to develop and enhance students’ conceptual and practical understanding of machine learning (ML) in the contexts of industry-relevant applications where ML has emerged to play a key role. The students will learn about fundamental concepts, key techniques and popular tools in ML as well as how real-world problems are cast into ML tasks. They will also acquire the ability to apply ML techniques and tools to solve industry-relevant problems.
|Unit Learning Outcomes|
|On successful completion of this unit students will be able to:|
|#||Unit Learning Outcome Description|
|ULO1||Demonstrate advanced knowledge of fundamental concepts, key techniques and popular tools in machine learning|
|ULO2||Critically evaluate the roles of machine learning in various real-world applications|
|ULO3||Critically analyse, evaluate and apply appropriate machine learning techniques and tools to solve various industry-relevant problems|
|ULO4||Communicate effectively as a professional to technical and non-technical audiences|