SubjectsSubjects(version: 953)
Course, academic year 2023/2024
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Seminar on advanced data analysis - NAIL125
Title: Seminář z pokročilé analýzy dat
Guaranteed by: Department of Theoretical Computer Science and Mathematical Logic (32-KTIML)
Faculty: Faculty of Mathematics and Physics
Actual: from 2022
Semester: summer
E-Credits: 3
Hours per week, examination: summer s.:0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: English, Czech
Teaching methods: full-time
Teaching methods: full-time
Note: you can enroll for the course repeatedly
Guarantor: doc. RNDr. Iveta Mrázová, CSc.
Annotation -
This subject is organized as a review and research seminar focused on contemporary topics from the area of neural networks, deep learning, social network analysis and data mining. It is primarily intended for PhD and MS students working on their dissertations and theses on related topics. Student presentations are based on previously published papers or their own work.
Last update: Hric Jan, RNDr. (28.05.2020)
Aim of the course -

By means of oral presentations, the seminar teaches students how to follow and understand recent results achieved in the area, how to solve relevant problems and present the obtained research results.

Last update: Hric Jan, RNDr. (28.05.2020)
Course completion requirements -

Credit is given for an own presentation of a student and his/her active participation at seminars (at least 80% of seminars attended). The credit cannot be repeated.

Last update: Hric Jan, RNDr. (28.05.2020)
Literature -

Conference proceedings

  • Conference on Neural Information Processing Systems (NeurIPS)
  • International Joint Conference on Neural Networks (IJCNN)
  • IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM)
  • Knowledge Discovery and Data Mining (KDD)


  • IEEE Transactions on Neural Networks and Learning Systems
  • Neural Networks, Neurocomputing
  • IEEE Transactions on Knowledge and Data Engineering
  • Social Network Analysis and Mining

Last update: Hric Jan, RNDr. (28.05.2020)
Teaching methods -

A seminar with oral reports, where students present current research results reviewed from the literature or their own results. It may involve solving of selected problems relevant to the area.

Last update: Hric Jan, RNDr. (28.05.2020)
Syllabus -

This seminar has no fixed syllabus. Its actual content consists of reviewing assigned papers and discussions of research topics that are the subject of master theses and doctoral dissertations - mainly in the field of neural networks, deep learning, social network analysis or data mining.

Last update: Hric Jan, RNDr. (28.05.2020)
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