Master's Programme in Information and Communication Technology
Artificial Intelligence, 5-year master programme
Language of instruction
English
Learning outcomes
On successful completion of the course, the student should:
know the concepts and terms of language description and use them correctly in arguments
be able to apply best practice of compilers and language processing
be able to design code generation from high-level descriptions
be able to analyse and design high-level language descriptions capturing all language aspects
be able to translate between languages, grammars and automata
Course contents
Model-driven development and Language descriptions
Tools for language development
Handling of structural, syntax and semantic language aspects
Code generator theory and application
Grammars, languages and automata
Teaching methods
Lectures, blackboard exercises, laboratory exercises, and self study. Some of the assignments will be compulsory.
Assessment methods and criteria
Portfolio. Graded assessment. Information about the content of the portfolio will be given in Canvas by the start of the semester.
Evaluation
The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.
Offered as Single Standing Module
Yes. Subject to availability or capacity.
Admission Requirement if given as Single Standing Module
Admission requirements are the same as for the master programme in Information and Communication Technology, the Information Technologies profile.