IN4080 – Natural Language Processing
Changes in the course due to coronavirus
Autumn 2020 the exams of most courses at the MN Faculty will be conducted as digital home exams or oral exams, using the normal grading scale. The semester page for your course will be updated with any changes in the form of examination.
The course gives a comprehensive overview over modern Natural Language Processing (NLP) with main emphasis on probabilistic and machine learning techniques. Methodology for experiments based on machine learning applied to language data together with evaluation of such experiments is central. The course includes an overview over typical NLP applications, like information extraction, machine translation, question-answering systems, and a more in-depth study of one such application. In addition, the steps in a typical NLP system, like tagging, parsing, named entity recognition, relation extraction will be considered. The course will prepare the students for a master´s thesis in Informatics: Language Technology.
After completing IN4080:
- You are familiar with the most central applications of Natural Language Processing (NLP) and have in-depth knowledge of at least one application
- You are familiar with the central research methods and technologies used in NLP
- You can carry out NLP experiments involving machine learning and evaluate the results
- You are familiar with the steps in a typical NLP system and you are able to select and apply tools for these steps
- You are familiar with the concept of probability and how it is applied in NLP methods and in evaluation
Admission to the course
Students admitted at UiO must apply for courses in Studentweb. Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.
Nordic citizens and applicants residing in the Nordic countries may apply to take this course as a single course student.
If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures for international applicants.
- 7 credits overlap with INF5830 – Natural language processing (continued).
Teaching: 2-6 hours a week, varying through the semester between lectures and lab sessions (non-obligatory).
There will be some mandatory projects which must be passed.
4 hours written digital exam
Examination support material
No examination support material is allowed.
Language of examination
You may write your examination paper in Norwegian, Swedish, Danish or English.
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester. Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.