KURSPLAN
State-of-the-Art in AI Research, 7,5 högskolepoäng
State-of-the-Art in AI Research, 7.5 credits
Kursplan för studenter höst 2020
Kurskod: TSAS20
Fastställd av: VD 2020-03-01
Gäller fr.o.m.: 2020-08-01
Version: 1
Utbildningsnivå: Avancerad nivå
Utbildningsområde: Tekniska området
Ämnesgrupp: DT1
Fördjupning: A1F
Huvudområde: Informatik

Lärandemål

After a successful course, the student shall

Kunskap och förståelse

- Display knowledge of novel methods, trends and challenges related to AI and machine learning that are of interest to the research community,
- Demonstrate comprehension of how to apply recent AI and machine learning methods to different kinds of problems and applications

Färdighet och förmåga

- Demonstrate the ability to search for literature outlining the state-of-the-art within AI and machine learning,
- Demonstrate the ability to analyse, present and critically review recent AI scientific work,
- Demonstrate the ability to produce a draft version of a scientific publication,

Värderingsförmåga och förhållningssätt

- Demonstrate the ability to critically assess scientific papers in relevant areas of AI.

Innehåll

The course goes into depth in terms of selected topics and methods within AI, machine learning and their applications. Examples may include areas, such as computational intelligence algorithms in search, optimization and classification, natural language processing and FAT (fairness, accountability, transparency) aspects. Examples of relevant applications could include robotics, music, health and medicine.

Undervisningsformer

The teaching in the course consists mainly of lectures and discussion seminars. The course content is based on contemporary developments in the AI field and presented by the course manager, members of the Jönköping AI Laboratory research group, invited guest speakers or the participants.

Undervisningen bedrivs på engelska.

Förkunskapskrav

Passed courses at least 90 credits within the major subject Informatics, and completed course Embedded and Distributed AI, 7,5 credits or equivalent. Proof of English proficiency is required.

Examination och betyg

Kursen bedöms med betygen 5, 4, 3 eller Underkänd.

The final grade for the course is based on a balanced set of assessments. The final grade will only be issued after satisfactory completion of all assessments.

Poängregistrering av examinationen för kursen sker enligt följande system:
ExaminationsmomentOmfattningBetyg
Presentationer2,5 hp5/4/3/U
Seminarier2,5 hp5/4/3/U
Utkast till artikel2,5 hp5/4/3/U

Övrigt

The examination consists of one or several presentations by the participants on a relevant state-of-the-art topic within the AI and machine learning domain, active participation in the discussion seminars and the preparation of a draft paper.

Kurslitteratur

Litteratur

The literature list for the course will be provided one month before the course starts.

Compulsory readings may include books, book chapters or journal/magazine/conference articles.