FI:PV212 Seminar on Dig.Typography - Course Information
PV212 Readings in Digital Typography, Scientific Visualization, Information Retrieval and Machine Learning
Faculty of InformaticsAutumn 2014
- Extent and Intensity
- 0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
- Teacher(s)
- doc. RNDr. Petr Sojka, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Petr Matula, Ph.D.
Department of Visual Computing – Faculty of Informatics
Contact Person: doc. RNDr. Petr Sojka, Ph.D.
Supplier department: Department of Visual Computing – Faculty of Informatics - Timetable
- Fri 10:00–11:50 C522
- Prerequisites
- SOUHLAS
Interest in research problems in areas of Machine Learning, Scientific Visualization, Information Retrieval and Digital Typography. Courage to learn how to move the human knowledge and understanding in these areas by CS research. Willingness to study particular topic of choice, and refer, discuss and brainstorm about it with others. - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Informatics (programme FI, B-AP)
- Applied Informatics (programme FI, N-AP)
- Information Technology Security (programme FI, N-IN)
- Bioinformatics (programme FI, B-AP)
- Bioinformatics (programme FI, N-AP)
- Information Systems (programme FI, N-IN)
- Informatics with another discipline (programme FI, B-BI)
- Informatics with another discipline (programme FI, B-EB)
- Informatics with another discipline (programme FI, B-FY)
- Informatics with another discipline (programme FI, B-GE)
- Informatics with another discipline (programme FI, B-GK)
- Informatics with another discipline (programme FI, B-CH)
- Informatics with another discipline (programme FI, B-IO)
- Informatics with another discipline (programme FI, B-MA)
- Informatics with another discipline (programme FI, B-SO)
- Informatics with another discipline (programme FI, B-TV)
- Informatics (eng.) (programme FI, D-IN4)
- Informatics (programme FI, B-IN)
- Informatics (programme FI, D-IN4)
- Informatics (programme FI, M-IN)
- Informatics (programme FI, N-IN)
- Mathematical Informatics (programme FI, B-IN)
- Parallel and Distributed Systems (programme FI, B-IN)
- Parallel and Distributed Systems (programme FI, N-IN)
- Computer Graphics and Image Processing (programme FI, B-IN)
- Computer Graphics (programme FI, N-IN)
- Computer Networks and Communication (programme FI, B-IN)
- Computer Networks and Communication (programme FI, N-IN)
- Computer Systems and Technologies (eng.) (programme FI, D-IN4)
- Computer Systems and Technologies (programme FI, D-IN4)
- Computer Systems and Data Processing (programme FI, B-IN)
- Computer Systems (programme FI, N-IN)
- Embedded Systems (eng.) (programme FI, N-IN)
- Programmable Technical Structures (programme FI, B-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (eng.) (programme FI, N-AP)
- Service Science, Management and Engineering (programme FI, N-AP)
- Social Informatics (programme FI, B-AP)
- Theoretical Informatics (programme FI, N-IN)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-SS)
- Upper Secondary School Teacher Training in Informatics (programme FI, M-TV)
- Upper Secondary School Teacher Training in Informatics (programme FI, N-SS) (2)
- Artificial Intelligence and Natural Language Processing (programme FI, B-IN)
- Artificial Intelligence and Natural Language Processing (programme FI, N-IN)
- Image Processing (programme FI, N-AP)
- Course objectives
- The aim of the seminar is a presentation of results of student research (both pregradual and gradual). At the end of the course students will have experience in presenting and discussion of their or other (from readings) research. Every student has to have her/his own presentation in the seminar.
- Syllabus
- Referred topics/projects for every year will be posted on the web page of the course, and negotiated with registered students. The lectures consist mostly of students' presentations. The presentations and discussion are either in Czech or, according to the preferences of the speaker, in English. The students can control the content of the seminar in the discussions after each presentation.
- Literature
- WITTEN, I. H. and Eibe FRANK. Data mining : practical machine learning tools and techniques. 2nd ed. Amsterdam: Elsevier, 2005, xxxi, 525. ISBN 0120884070. info
- MITCHELL, Tom M. Machine learning. Boston: McGraw-Hill, 1997, xv, 414. ISBN 0070428077. info
- Information retrieval :data structures & algorithms. Edited by William B. Frakes - Ricardo Baeza-Yates. Upper Saddle River: Prentice Hall, 1992, viii, 504. ISBN 0-13-463837-9. info
- KNUTH, Donald Ervin. Digital typography. Stanford: Center for the Study of Language and Information, 1999, xv, 685. ISBN 1575860112. info
- Teaching methods
- Lectures intermixed with seminar style discussions and brainstormings to solve given research problems. Students will be given readings as a preparation for the contact teaching hours, if they will not come with their own research problems.
- Assessment methods
- Every student will either refer about some research topic from readings or solve some project and present its solution. Students must attend the seminar regularly and take active part in the seminar discussions.
- Language of instruction
- English
- Follow-Up Courses
- Further comments (probably available only in Czech)
- The course is taught annually.
- Teacher's information
- http://www.fi.muni.cz/~sojka/PV212/
- Enrolment Statistics (Autumn 2014, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2014/PV212