Učni načrt predmeta

Predmet:
Seminar II
Course:
Seminar II
Študijski program in stopnja /
Study programme and level		 Študijska smer /
Study field		 Letnik /
Academic year		 Semester /
Semester
Informacijske in komunikacijske tehnologije, 3. stopnja / 2 4
Information and Communication Technologies, 3rd cycle / 2 4
Vrsta predmeta / Course type
Obvezni / Mandatory
Univerzitetna koda predmeta / University course code:
IKT3-784
Predavanja
Lectures		 Seminar
Seminar		 Vaje
Tutorial		 Klinične vaje
work		 Druge oblike
študija		 Samost. delo
Individ. work		 ECTS
30 30 840 30

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
prof. dr. Nada Lavrač
Sodelavci / Lecturers:
Jeziki / Languages:
Predavanja / Lectures:
Slovenski ali angleški / Slovene or English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisites:

Zaključen študij druge stopnje s področja informacijskih ali komunikacijskih tehnologij ali zaključen študij druge stopnje na drugih področjih z znanjem osnov s področja predmeta. Potrebna so tudi osnovna znanja matematike, računalništva in informatike.

Completed second-cycle studies in information or communication technologies or completed second-cycle studies in other fields with knowledge of fundamentals in the field of this course. Basic knowledge of mathematics, computer science and informatics is also requested.

Vsebina:
Content (Syllabus outline):

Študenti bodo razvili sposobnosti spremljanja ter prepoznavanja aktualnih znanstveno raziskovalnih problemov, sodobnih metod raziskovanja, najnovejših rezultatov in uporabe najnovejšega znanja na področju informacijskih in komunikacijskih tehnologij. Študenti se bodo soočili tudi z izzivi izdelave pisnega pregleda obravnavanih vsebin v obliki osnutka članka in osnutka teme disertacije ter s posredovanjem ugotovitev v obliki neposrednega ustnega komuniciranja.

Students will develop the ability to follow and identify current scientific research problems, modern methods of research, the latest results and the use of the state-of-the-art knowledge in the field of information and communication technologies. Students will also face with the challenges of writing a written review of the selected topics as a draft paper and a draft topic of the dissertation as well as by sharing of their findings with oral seminar presentation.

Temeljna literatura in viri / Readings:

Znanstvena literatura s področja raziskovalnega dela študenta. / Scientific literature from the field of the
student’s own research.

Cilji in kompetence:
Objectives and competences:

Predmet nadgrajuje pridobljeno znanje pri predmetu Seminar I, cilj predmeta je pripraviti pisno celostno predstavitev svojih raziskovalnih rezultatov v obliki osnutka članka in osnutka teme disertacije ter posredovanje navedenega v obliki ustne predstavitve.

This course upgrades the knowledge received at Seminar I, its aim is to prepare a written comprehensive presentation of the research results as a draft paper and a draft topic of doctoral dissertation. An important goal is also the ability to present their findings in the form of oral presentation.

Predvideni študijski rezultati:
Intendeded learning outcomes:

Priprava osnutka članka in osnutka teme disertacije, ustna predstavitev ter suverena komunikacija o obravnavanih vsebinah.

Preparation of a draft paper and a draft topic of doctoral dissertation as well as oral presentation and sovereign communication about the discussed topics.

Metode poučevanja in učenja:
Learning and teaching methods:

Seminar, konzultacije, druge metode.

Seminar, consultations, other methods.

Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Seminarska naloga (osnutek članka s področja doktorske disertacije)
70 %
Seminar (draft paper on the topic of the doctoral dissertation)
Ustna predstavitev in zagovor seminarske naloge
30 %
Oral presentation and defense of the seminar work
Seminar II študent opravi tako, da pred komisijo treh profesorjev predstavi svoje raziskovalno delo na doktorskem študiju. Z mentorjem uskladi datum in uro seminarja ter na info@mps.si najmanj en teden pred predstavitvijo sporoči datum, uro, prostor in naslov seminarja. Komisija je praviloma enaka komisiji za oceno teme disertacije. Po opravljenem Seminarju II odda v tajništvo MPŠ izpolnjen in podpisan zapisnik Seminarja II, izpitno prijavnico za Seminar II, seminarsko nalogo (osnutek članka s področja doktorske disertacije) ter natisnjene prosojnice seminarja.
Seminar II assessment is based on the presentation of the student's doctoral project in front of a committee of three IPS professors. The student and the supervisor jointly set the date and time of the seminar. At least one week before the presentation, the student shall communicate the date, time, room and title of the seminar to info@mps.si. The commission is in principle the same as commission for the evaluation of the topic of the dissertation. After presenting Seminar II, the student must submit to the IPS Secretariat the filled out and signed minutes of Seminar II, Seminar II exam application, printed seminar work (draft paper on the topic of the doctoral dissertation), as well as printout of slides presented at the seminar.
Reference nosilca / Lecturer's references:
1. ŠKRLJ, Blaž, BEVEC, Matej, LAVRAČ, Nada. Multimodal AutoML via representation evolution. Machine learning and knowledge extraction. Mar. 2023, iss. 1, vol. 5, str. 1-13, ilustr. ISSN 2504-4990
2. ŠKRLJ, Blaž, KRALJ, Jan, KONC, Janez, ROBNIK ŠIKONJA, Marko, LAVRAČ, Nada. Deep node ranking for neuro-symbolic structural node embedding and classification. International journal of intelligent systems. [Print ed.]. 2022, vol. 37, iss. 1, str. 914-943, ilustr. ISSN 0884-8173
3. ŠKRLJ, Blaž, DŽEROSKI, Sašo, LAVRAČ, Nada, PETKOVIĆ, Matej. ReliefE : feature ranking in high dimensional spaces via manifold embeddings. Machine learning. [Print ed.]. 2022, vol. 111, no. 11, str. 273-317. ISSN 0885-6125
4. ŠKRLJ, Blaž, ERŽEN, Nika, LAVRAČ, Nada, KUNEJ, Tanja, KONC, Janez. CaNDis : a web server for investigation of causal relationships between diseases, drugs, and drug targets. Bioinformatics. [Print ed.]. 1 Sep. 2021, vol. 36, no. 6, str. 885-887, ilustr. ISSN 1367-4803
5. J. Fürnkranz, D. Gamberger, and N. Lavrač, Foundations of Rule Learning. Springer, 2012.