Welcome to Accelerated Natural Language Processing
PLEASE READ: Urgent note regarding ANLP timetable
This course synthesizes ideas from linguistics and computer science to provide students with a fast-paced introduction to the field of natural language processing. We cover a range of foundational concepts, theoretical and computational models of language, and linguistic phenomena. We focus on what makes automatic processing of language unique and challenging: its statistical properties, complex structure, and pervasive ambiguity. We use English as the primary exemplar throughout, but also discuss similarities and differences to other languages, and the implications for computational models.
As we progress from lower levels of linguistic structure (words and morphemes) through syntax to semantics and discourse, we cover formal models and algorithms for representing and analysing these different types of structure (e.g., n-gram models, HMMs, probabilistic grammar, and word embeddings). These methods form the conceptual foundation for understanding state-of-the-art approaches, which are covered in depth in the Semester 2 follow-on course NLU+. We also introduce methodological and ethical considerations (e.g., evaluation, data collection, algorithmic bias) that are important for research and practice in the field.
Is this course right for me?
Read the page below for more information about what background is needed, how you can prepare, and how this course relates to other courses in Informatics.
This course is a required pre-requisite for NLU+ in semester 2. Really, we mean it. The only exception to this is if you have previously taken an NLP course that covers the same material, including both linguistics and algorithms (which is very rare), and you receive permission. Please see the list of topics in the syllabus and if you are really convinced you know it all, speak to the instructor.
Course syllabus and activities summary
The syllabus provides a rough week-by-week outline of the course, as well as information about what is expected of you, how to make the most of this course, and the tools and structure we plan to use to deliver the course this year.
The course syllabus provides detailed information on what you can expect from the course and from us. The activities summary gives an overview of weekly course activities, indicating what's required and what's optional, and also has a 1-page week-by-week schedule of activities for the course.
Where do I find things?
On this site, you will find publicly available information:
- a plan for each week, including
- assigned readings
- lecture slides
- tutorial sheets and solutions
- lab sheets and solutions
- quiz sheets and solutions
- the course syllabus
- other materials provided by the instructors
On the course learn site (linked at the top of this page) you will find information that requires a university login:
- all information about assessment, including
- instructions and downloads
- due dates and late policy
- links to submission inboxes
- a link to the course discussion forum