Course overview
In this course, the students will learn about the fundamentals of machine learning and how to utilise and apply some of the most commonly used tools. The students will learn how to create software that allows the use of pre-existing tool kits when appropriate in order to solve a variety of machine learning problems. The course will have a strong practical component, with case studies and worked examples being used to emphasise the importance of legitimate and verifiable solutions.
Course learning outcomes
- Adapt industry-standard software tools to model and solve machine learning tasks on real data sets.
- Evaluate and identify an appropriate method and tool for a given problem and data set.
- Discriminate between problems and data sets that are amenable to machine learning methods and those that are not.
- Analyse results and solutions to verify their correctness and identify sources of error.
- Assess the significance and validity of solutions obtained by multiple methods.
- Design data management procedures to enable the accurate application of machine learning.