Title of course: Technical informatics, lecture
Code: TTGME7012_EN
ECTS Credit points: 3
Type of teaching, contact hours
- lecture: 2 hours/week
- practice: -
- laboratory: -
Evaluation: exam
Workload (estimated), divided into contact hours:
- lecture: 28 hours
- practice: -
- laboratory: -
- home assignment: 22 hours
- preparation for the exam: 40 hours
Total: 90 hours
Year, semester: 1st year, 2nd semester
Its prerequisite(s): -
Further courses built on it: -
Topics of course
The aim of the course is to familiarise students with the most important elements and technologies of systems based on modern communication technologies, with an emphasis on the broad basics, the physical/technical foundations of the technologies and their interrelationships, rather than on detailed descriptions. The knowledge acquired during the course provides a sufficient theoretical basis for further advanced knowledge and for the formal management and practical implementation of basic hardware and software tasks. The following topics will be covered during the semester: basic network concepts, terminology, overview of network services; basic communication concepts (transmission, types, communication modes), data communication tasks, evolution of data communication networks, architecture. basic concepts of data communication; transmission, interconnection and connection modes, network addressing and services; layered implementation of systems; reference models (OSI, TCP/IP), messages, packets, messaging through layers; application layer of the OSI model, DNS namespace structure and name resolution. recursive and iterative name resolution; transport layer of the OSI model, UDP and TCP protocols, connection management, reliable data transmission; network layer of the OSI model, IP addressing mechanisms, classes and subnets, routing, details of the routing process; the data link layer of the OSI model, network channel allocation, channel management protocols, ARP address resolution protocol, data fragmentation; the physical layer of the OSI model, technical implementation of data transmission, cable types, physical basis of technical implementation, metallic and optical wired, wireless transmission. Networking tools, networking, signal coding methods; precision location based analysis and automation in field data collection; Big Data technology and its applications in geospatial analysis; Machine Learning or the role of Machine Learning in geoinformatics; Internet of Things - sensor systems: new data collection opportunities in geoinformatics.
Literature
- Japkowicz, N. - Stefanowski, J. 2016. Big Data Analysis: New Algorithms for a New Society, Springer
- Baesens, B. 2014. Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, Wiley
Requirements:
- for a signature
Attendance at lectures is recommended, but not compulsory. In the end of the semester there is one final test.
- for a grade
The course ends in an examination. The exam grade is the result of the examination. The minimum requirement for the examination is 50%. Based on the score of the test the grade for the examination is given according to the following table:
| Score | Grade |
| 0-49 fail | (1) |
| 50-64 pass | (2) |
| 65-74 satisfactory | (3) |
| 75-85 good | (4) |
| 86-100 excellent | (5) |
If the score of any test is below 50, students can take a retake test in conformity with the EDUCATION AND EXAMINATION RULES AND REGULATIONS.
Person responsible for course: Dr. Gábor Négyesi, PhD, Assistant Professor
Lecturer: Dr. László Bertalan, PhD, Assistant Professor