IN4080 – Natural Language Processing

Schedule, syllabus and examination date

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Course content

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.

Learning outcome

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

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.

Overlapping courses

7 credits overlap with INF5830 – Natural language processing (continued)

Teaching

Teaching: 2-6 hours a week, varying through the semester between lectures and lab sessions (non-obligatory).

There will be some obligatory projects which must be passed.

Examination

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.

Grading scale

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.

Explanations and appeals

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.

Withdrawal from an examination

It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.

It will also be counted as one of your three attempts to sit the exam for this course, if you sit the exam for one of the following courses:

Special examination arrangements

Application form, deadline and requirements for special examination arrangements.

Facts about this course

Credits

10

Level

Master

Teaching

Every autumn

Examination

Every autumn

Teaching language

English