TDT4310 - Intelligent Text Analytics and Language Understanding


Examination arrangement

Examination arrangement: Aggregate score
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
Assignment 75/100
School exam 25/100 4 hours D

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 to text analytics.

Learning methods and activities

Lectures and exercises. The subject requires an approved project report with theoretical and experimental content. The lectures will be given in English, unless all students speak Norwegian.

Compulsory assignments

  • Assignments

Further on evaluation

A written exam (25%) and project work (75%) 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.

Exercises from earlier years may be approved by agreement with the course coordinator.

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

Course materials

Information will be given at the beginning of the course.

More on the course

Version: 1
Credits:  7.5 SP
Study level: Second degree level


Term no.: 1
Teaching semester:  SPRING 2024

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • 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: Lecturer(s):

Department with academic responsibility
Department of Computer Science


Examination arrangement: Aggregate score

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Spring ORD School exam 25/100 D INSPERA
Room Building Number of candidates
Spring ORD Assignment 75/100 INSPERA
Room Building Number of candidates
Summer UTS School exam 25/100 D INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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