TDP030 · 6 credits · Basic level (G2F) · Datavetenskap, Programmering
Language Technology
Active · next start VT 2027
89%
passed the latest ordinary exam
DIT1 · 20 Mar 2026 · 35 students
81%
passed the ordinary exams, all sittings over the last 5 years
DIT1 · 115 students
24%
Harder than 24% of courses at basic level
Compared with 874 courses at the same level, ordinary exams over the last three academic years. 63 students.
Part of 1 programme
Exam
DIT1 Digital written examination
- 5
- 4
- 3
- U
Ordinary exams
81% passed · 115 students
- 89%35
- 93%28
- 76%21
- 73%15
- 56%16
Re-exams
83% passed · 6 students
- 83%6
- Pass the re-exam: 83% (6 students), compared with 81% (115 students) on the ordinary exam
- Get 4 or 5: 31% (121 students)
Show small sittings (8)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 75%4
- 100%1
- 100%4
- 0%2
- 100%2
- 50%2
- 0%2
- 50%2
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
UPG1 Project assignments
- 5
- 4
- 3
- U
Main rounds
65% passed · 84 students
- 69%29
- 75%20
- 47%15
- 65%20
Later rounds
94% passed · 50 students
- 92%37
- 100%7
- 100%6
- Pass a later round: 94% (50 students), compared with 65% (84 students) on the ordinary exam
- Get 4 or 5: 55% (134 students)
Show small sittings (4)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
- 100%1
- 100%4
- 100%4
Hand-in or lab
LAB1 Practical assignments
- 5
- 4
- 3
- U
Main rounds
83% passed · 88 students
- 100%32
- 79%19
- 50%16
- 86%21
Later rounds
98% passed · 45 students
- 100%7
- 100%30
- 88%8
- Pass a later round: 98% (45 students), compared with 83% (88 students) on the ordinary exam
- Get 4 or 5: 23% (133 students)
Show small sittings (4)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
- 100%2
- 100%1
About the course
Aim
Language technology develops methods for making human language accessible to computers. The goal of this course is to provide an introduction to language technology as an application area, and to some of its basic methods. The course focuses on methods based on machine learning.
On completion of the course, the student should be able to:
- explain basic methods for the processing of natural language
- practically apply language technology methods and systems to realistic problems
- evaluate language technology components and systems with appropriate methods
- assess the difficulty of language technology problems and which resources are needed to solve them
- reason about the capabilities and limitations of large language models for solving language technology problems
Content
- basic methods and techniques for the analysis and interpretation of natural language
- relevant machine learning methods
- validation methods
- applications of language technology
- tools, software libraries, and data
- Examiner
- Marcel Bollmann
- Scheduled hours
- 48 h
- Main field of study
- Datavetenskap, Programmering