Information on the Natural Language Processing specialist area.
The aim of the Natural Language Processing specialist area is to prepare students for entry into PhD programmes or for employment in industrial laboratories undertaking research and development in natural language and speech processing.
Students registered in this Specialist Area are recommended to select at least fifty credit points from these courses, including the core courses. Students are encouraged to take courses in speech processing or psycholinguistics from the School of Philosophy, Psychology and Language Sciences (PPLS); see the optional external courses list below. Courses are subject to availability.
Preparation advice: If you haven't programmed in Python before, we recommend you start to learn it before you arrive. Find an online (or local college) tutorial at your level. The Computer Programming for Speech and Language Processing starts from scratch, but learning to program well takes time: starting early will help you. We also recommend you buy the core text for some Semester 1 courses: Speech and Language Processing, 2nd Edition, Jurafsky and Martin. Any reading you do from this text before you arrive will help you get started.
|Semester 1||Semester 2|
|Core Courses (see notes below)|
Accelerated Natural Language Processing (20 credits)
Introductory Applied Machine Learning (20 credits, level 10)
Machine Learning and Pattern Recognition (20 credits)
Machine Translation (20 credits)
|Optional External Courses|
Notes on core courses: Accelerated Natural Language Processing (20pts) is core for all students. Computer Programming for Speech and Language Processing should be taken rather than another programming course, to fulfill the programming requirement (unless exempted by your Personal Tutor). Speech Processing is core for students wishing to study both speech and text processing. Introductory Applied Machine Learning is not marked as core, but is recommended for those with sufficient maths background.
Register promptly for external courses. They can have limited numbers, earlier deadlines than Informatics, and course materials on Learn are only available after registering.