Entry requirements

Mathematics for Language Technologists or equivalent

Learning outcomes

In order to pass the course, a student must be able to:

1. apply basic principles of machine learning to natural language data;
2. evaluate the performance of machine learning schemes;
3. use standard off-the-shelf software for machine learning;
4. apply supervised and unsupervised models for classification.

Assessment

The course is examined by means of shorter lab assignments completed in class and three larger assignments.

Information on the content and format of the assignments, the date of completion/submission and re-examination is given at the start of the course by the course coordinator.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator.