PV177 Laboratory of Advanced Network Technologies

Faculty of Informatics
Spring 2019
Extent and Intensity
0/2/0. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Eva Hladká, Ph.D. (lecturer)
RNDr. Milan Čermák, Ph.D. (lecturer)
RNDr. Martin Laštovička (lecturer)
prof. RNDr. Václav Matyáš, M.Sc., Ph.D. (lecturer)
RNDr. Tomáš Rebok, Ph.D. (lecturer)
Mgr. Ing. Jakub Čegan (seminar tutor)
RNDr. Martin Drašar, Ph.D. (seminar tutor)
RNDr. Martin Macák (seminar tutor)
RNDr. Valdemar Švábenský (seminar tutor)
Guaranteed by
doc. RNDr. Eva Hladká, Ph.D.
Department of Computer Systems and Communications - Faculty of Informatics
Contact Person: doc. RNDr. Eva Hladká, Ph.D.
Supplier department: Department of Computer Systems and Communications - Faculty of Informatics
Timetable of Seminar Groups
PV177/DataScience: Thu 21. 2. to Thu 16. 5. Thu 10:00–11:50 A505, M. Macák, T. Rebok
Prerequisites
SOUHLAS
Specialization "Big Data Analytics in Practice" - none
Specialization "Computer Networks" - completed PB156, preferably also PA159
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
there are 39 fields of study the course is directly associated with, display
Course objectives
Familiarization with the area and practical team project aimed at adopting the principles in one of the areas, which the course is specialized on in the particular semester.
In spring 2019, the course is specialized in the following areas:
1. Big Data analytics in practice -- the aim of this course's specialization is to introduce students to methods and tools for analyzing large data volumes (so-called Big Data), which will then be examined in the form of practical projects presented at the end of the semester.
2. Advanced Computer Networks -- the aim of this specialization is to introduce students to the area of computer networks and related technologies, research methodology, own research and presentation of results. The work is separated into two semesters, begin in the fall semester with lower network levels (physical infrastructure, construction of computer halls, basic protocols from level two = STP, 802.1Q,...), in spring semester work follows with protocols on L3, mostly routing protocols (OSPF, BGP). Sprig semester follows the fall.
Syllabus
  • Team project in one of the areas, which the course is specialized on in the particular semester: Big Data analytics, computer networks, grids or multimedia. Students can choose or are assigned a practical project (team-based, i.e. an assignment will be solved by a group of students). When solving the project, students will master the advanced understanding of a subject, acquire basic research methodology, will optionally perform the research and will present achieved results. The work progress will be evaluated on regular weekly or two-weekly seminars, where students will receive the necessary feedback on their undertakings.
  • The last seminar will be devoted to the overall evaluation and students will receive credits.
Literature
  • STEVENS, W. Richard, Bill FENNER and Andrew M. RUDOFF. UNIX network programming. 3rd ed. Boston, Mass.: Addison-Wesley, 2004. xxiii, 991. ISBN 0-13-141155-1. info
  • KUROSE, James F. Computer networking :a top-down approach featuring the Internet. Boston: Addison-Wesley, 2003. xvii, 752. ISBN 0-321-17644-8. info
  • GOUDA, Mohamed G. Elements of network protocol design. New York: John Wiley & Sons, 1998. xviii, 506. ISBN 0471197440. info
Teaching methods
There are several projects and each student works on one of them often in cooperation with others. Students explore the given theme during the semester. During seminars, students will refer about their results in the project. Some course specializations may be supplemented with introductory lectures on the particular topic.
Assessment methods
Students are evaluated according to their activity on seminars, and the quality of achieved results and their presentations in front of their peers.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught each semester.
The course is also listed under the following terms Autumn 2005, Spring 2006, Autumn 2006, Spring 2007, Autumn 2007, Spring 2008, Autumn 2008, Spring 2009, Autumn 2009, Spring 2010, Autumn 2010, Spring 2011, Autumn 2011, Spring 2012, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, Autumn 2017, Spring 2018, Autumn 2018, Autumn 2019, Spring 2020, Autumn 2020, Spring 2021.
  • Enrolment Statistics (Spring 2019, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2019/PV177