course-details-portlet

TDT4310

Intelligent Text Analytics and Language Understanding

Assessments and mandatory activities may be changed until September 20th.

Credits 7.5
Level Second degree level
Course start Spring 2026
Duration 1 semester
Language of instruction English
Location Trondheim
Examination arrangement Aggregate score

About

About the course

Course content

The subject comprises: human languages and language processing, machine learning and statistical methods for language understanding and text analytics, text classification and deep learning, sentiment analysis and opinion mining, information access and text mining, conversational agents, machine translation, computational semantics, computational linguistic creativity.

Learning outcome

Students should have a basic and hands-on understanding of the currently used frameworks and methods for text analytics and natural language understanding, in particular the application of machine learning methods and large language models to text analytics and generation.

Learning methods and activities

The course consists of lectures, a set of smaller programming exercises (non-graded but obligatory), a larger programming project (graded), and a written exam. The subject thus requires an approved project report with theoretical and experimental content related to the currently most topical themes in the field. The highlights of the project should be presented to the other students (with obligatory attendance on a subset of the presentations). The lectures, presentations and exam will be given in English, unless all students speak Norwegian.

Compulsory assignments

  • Assignments

Further on evaluation

A written exam (50%) and project work (50%) form the basis for the final grade in the course. The parts and the entire course are assigned letter grades.

If there is a re-sit examination, the examination form may change from written to oral.

When repeating the course, all partial assessments must be repeated.

Required previous knowledge

TDT4110 ("Information Technology, Introduction") or equivalent.

Students lacking TDT4110 need to contact the lecturer to register for TDT4310.

See also the recommended previous courses.

Course materials

Information will be given at the beginning of the course.

Subject areas

  • Computer and Information Science
  • Applied Information and Communication Technology
  • Computer Science
  • Knowledge Systems
  • Information Systems
  • Computer Systems
  • Applied Linguistics
  • Applied Linguistics
  • Information Technology and Informatics
  • Communication and Information Science
  • Languages, Logics and Inform. Technology

Contact information

Course coordinator

Lecturers

Department with academic responsibility

Department of Computer Science

Examination

Examination

Examination arrangement: Aggregate score
Grade: Letter grades

Ordinary examination - Spring 2026

School exam
Weighting 50/100 Examination aids Code D Duration 4 hours Exam system Inspera Assessment Place and room Not specified yet.
Assignment
Weighting 50/100 Exam system Inspera Assessment

Re-sit examination - Summer 2026

School exam
Weighting 50/100 Examination aids Code D Duration 4 hours Exam system Inspera Assessment Place and room Not specified yet.