FI:PV177 Laboratory of Networks - Course Information
PV177 Laboratory of Advanced Network Technologies
Faculty of InformaticsAutumn 2019
- Extent and Intensity
- 0/2/0. 2 credit(s). Type of Completion: z (credit).
- Teacher(s)
- doc. RNDr. Eva Hladká, Ph.D. (lecturer)
prof. RNDr. Václav Matyáš, M.Sc., Ph.D. (lecturer)
RNDr. Tomáš Rebok, Ph.D. (lecturer)
RNDr. Martin Macák, Ph.D. (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 14:00–15:50 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 81 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 autumn 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. - Learning outcomes
- Getting new knowledge in the chosen area of interest and working on a practically-oriented team project.
- 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
- English
- Further Comments
- Study Materials
The course is taught each semester.
- Enrolment Statistics (Autumn 2019, recent)
- Permalink: https://is.muni.cz/course/fi/autumn2019/PV177