MSc in Artificial Intelligence and Language Technology

Artificial intelligence (AI) is a research and development field concerned with building smart machines capable of performing tasks that typically require human intelligence. Language Technology (LT) is a research and development field whose purpose is to develop tools that can process and understand human languages and facilitate their use in human-computer interaction.

Overview

A teacher stands in front of a class

Credits

120 ECTS.

Language

Language of instruction is English.

Length of study

Two years, full time.

Start date:

January and August each year.

 

The Master program in Artificial Intelligence and Language Technology (MAILT) at Reykjavik University (RU) is a two year interdisciplinary program. Students take courses in Computer Science and Engineering at RU, and courses from the MA program in LT at the University of Iceland (UI). The goal of the program is twofold. First, to graduate students with the necessary knowledge to manage and/or implement AI and LT projects. Second, to prepare students for PhD studies in the field of AI and LT.

Students need to be registered in the MAILT program at RU or in the MA program in LT at UI, but can pursue relevant courses in both universities. A student graduates from the university he/she is registered in, and produces a final masters project/thesis under the supervision of a researcher in that particular university. A student registered at RU graduates with an MSc degree, whereas a student registered at UI graduates with an MA degree.

Admission

  • BSc degree in Computer Science or a related field is required.

  • Students whose first degree is not in Computer Science may be required to complete preparatory classes from the undergraduate Computer Science degree at Reykjavik University.

Supporting documents

  • CV/résumé

  • Official university transcript/s, including educational career and academic results.

  • Submission of a letter of motivation (approx. 300 words) that includes reasoning for pursuing graduate work and academic goals.

  • Two academic references. You should select two referees who can provide an informed view of your academic or professional ability and suitability for your chosen programme of study. The letters of recommendation should be sent directly to telmas@ru.is.

  • Applicants are only invited to an interview after they have sent all necessary documents.

English language test score certificate (non-native speakers only)

You should upload a scanned copy of the original English language test certificate. If you do not have test results at the time of applying, you should submit your application without these scores and send them to us separately once available.

Language test waiver

The requirement to provide English proficiency scores may be waived, in cases where you have successfully completed, or are currently completing, a full-time degree-level course of a minimum of nine months at a recognised institution where the medium of instruction and assessment is entirely in English. If you wish to apply for a waiver of the English language test requirement, you will need to upload a letter with your application outlining the reasons why you should be exempted.

Structure 

Course Structure at RU

The MAILT program is a two year, 120 ECTS, study. At least 2/3 of the required course credits must be from graduate courses in Computer Science, Engineering, or from the MA program in LT at UI.

The program has two tracks: a course-based track and a research-based track. In the course-based track, students complete at least 90 ECTS of course-work, and 30 ECTS of M.Sc. project work under the supervision of a faculty member. In the research-based track, students complete at least 60 ECTS of course-work, while 60 ECTS are devoted to an individual research project under the supervision of a faculty member. Please view the module handbook for more information.  

Course-based track

1. Semester 2. Semester 3. Semester 4. Semester
T-725-MALV, Natural Language Processing (8 ECTS) - Mandatory  T-701-REM4, Research Methods (8 ECTS) - Mandatory T-738-VIEN, Virtual Humans (8 ECTS)  Master's thesis (30 credits)
T-809-DATA, Data Mining and Machine Learning (8 ECTS) - Mandatory, or T-796-DEEP) T-754-SPLP, Spoken Language Processing (8 ECTS) - Mandatory T-720-ATAI, Advanced Topics in AI (8 ECTS)  
T-796-DEEP, Introduction to Deep Learning (6 ECTS) - Mandatory, or T-809-DATA)  T-717-SPST, Speech synthesis, (6 ECTS) T-718-ATSR, Automatic Speech Recognition (8 ECTS)   
MLT301F, The structure of Icelandic and language technology, 10 ECTS (Taught at UI) MLT801F, Automatic language correction, 10 ECTS (taught at UI) MLT302F, Treebanks, 10 ECTS (Taught at UI)   
 32 ECTS 32 ECTS  34 ECTS   30 ECTS

*Conditional selection

Research-based track

1. Semester 2. Semester 3. Semester 4. Semester
T-725-MALV, Natural Language Processing (8 ECTS) - Mandatory  T-701-REM4, Research Methods (8 ECTS) - Mandatory

Master's thesis (30 credits)

Master's thesis (30 credits)
T-809-DATA, Data Mining and Machine Learning (8 ECTS) - Mandatory, or T-796-DEEP) T-754-SPLP, Spoken Language Processing (8 ECTS) - Mandatory
 
T-796-DEEP, Introduction to Deep Learning (6 ECTS) - Mandatory, or T-809-DATA)  T-717-SPST, Speech synthesis, (6 ECTS)
 
MLT301F, The structure of Icelandic and language technology, 10 ECTS (Taught at UI) MLT801F, Automatic language correction, 10 ECTS (taught at UI)
 
 32 ECTS 32 ECTS  30 ECTS   30 ECTS

*Conditional selection 

Autumn:

  • T-725-MALV, Natural Language Processing, 8 ECTS (Mandatory)
  • T-809-DATA, Data Mining and Machine Learning, 8 ECTS (Mandatory, or T-796-DEEP)
  • T-796-DEEP, Introduction to Deep Learning, 6 ECTS (Mandatory, or T-809-DATA)
  • T-718-ATSR, Automatic Speech Recognition, 8 ECTS
  • MLT301F, The structure of Icelandic and language technology, 10 ECTS (Taught at UI)
  • MLT302F, Treebanks, 10 ECTS (Taught at UI)
  • T-720-ATAI, Advanced Topics in AI, 8 ECTS
  • T-738-VIEN, Virtual Humans, 8 ECTS
  • T-740-SPMM, Software Project Management, 8 ECTS
  • T-768-SMAI, Informed Search Methods in AI, 8 ECTS
  • T-636-SMAT, Human Computer Interaction, 6 ECTS (BSc course)
  • T-519-STOR, Theory of Computation, 6 ECTS (BSc course)
  • T-603-THYD, Compilers, 6 ein. (BSc course)
  • ÍSL321G, Clauses and context, 10 ECTS (BSc course, taught at UI)
  • ÍSL306G, Phonetics, 10 ECTS (BSc course, taught at UI)
  • ÍSL314G, Phonology, 10 ECS (BSc course, taught at UI)

Spring:

  • T-701-REM4,Research Methods, 8 ECTS (Mandatory)
  • T-754-SPLP, Spoken Language Processing, 8 ECTS (Mandatory)
  • T-703-MGHR, Language Resources: research and development, 8 ECTS
  • T-717-SPST, Speech synthesis, 6 ECTS
  • MLT801F, Automatic language correction, 10 ECTS (taught at UI)
  • T-747-RELE, Reinforcement Learning, 8 ECTS
  • T-764-DATA, Big Data Management, 8 ECTS
  • T-742-CSDA, Computer Security, 8 ECTS
  • T-705-EACS, Ethics and Accountability in Computer Science
  • T-622-ARTI, Artificial Intelligence, 6 ECTS (BS course, Mandatory)
  • T-611-NYTI, New Technology, 6 ECTS (BSc course)
  • T-501-FMAL, Programming Languages, 6 ECTS (BSc course)
  • ÍSL440G, Syntax, 10 ECTS (BSc course, taught at UI)
  • ÍSL447G, Morphology, 10 ECTS (BSc course, taught at UI)
  • ÍSE025G, Icelandic - the basics, 10 ECTS (BSc course, taught at UI)

Contact us

 If you have any questions or want to obtain more information about studies at the School of Computer Science at Reykjavik University please contact: td@ru.is


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