Written assignments help the students to apply the principles of scientific research (including academic language usage) when planning their own master's thesis, and to get an understanding of the process, stages and types of research. The discussions carried out in seminars provide the students with an understanding of the principles of choosing research subjects or research material in accordance with the research plan and the principles of ensuring the trustworthiness of research. In practical classes, students practise searching scientific databases for sources of literature. In seminars, critical evaluation of sources of literature on the basis of checklists is also practised as well as producing arguments with regard to their own evaluations. An overview of the literature for the planned master's thesis is prepared individually. Practical written assignments enable the students to practise the planning of a research paper, drawing up a research plan and evaluating it critically, involving peer review. Data protection and cyber hygiene topics are discussed, and documents are prepared for applying for research approvals and for carrying out research.

Main concepts of telecommunication, transmitting messages and signals. Telecommunication systems, classification and main elements. Models for describing communication systems (incl. Shannon-Weaver, ISO-OSI, ARPA model). Source coding, channel coding, modulator, physical communication channel. Signals and spectrums. Digital signals, transmission of digital signals in communication channel. Different transmission media and solutions provided on their basis. Resource distribution in a communication channel, compression methods. Stream and error management, addresses and management of address space. Structure of IP networks., main parameters and limitations of network nodes. Software-based core networks with high throughput. Mobile access networks: WCDMA, OFDMA, LTE. Wireless communication. Security and reliability of telecommunication networks. Economical limitations of communications services.

The nature of big data and its potential for solving complex problems. Field courses related to big data. The Nature of the Data Industry. models, regulations.

1. Principles of Big Data Phonmena: What is Big Data? What are the main characteristics of Big Data? What are the main sources and application domains for Big Data?. 2. NoSQL and Big Data Storage Systems: What are the main principles, design decisions and trade-offs of NoSQL systems? What are the main categories of NoSQL systems? 3. Batach Processing Systems for Big Data: Hadoop, Spark, Flinl. Distributed Databses and Parallel Databases. 4. Big Stream Processing Systems: Challenges, requirements and systems for processing massive amounts of streaming data in real-time. 5. Big Graph Processing: What are the main challenges of distributed graph processing? What are the adeqaute programming models/ data storage techniques for distibuted graph procesisng? 6. Big Machine/Deep Learning Systems: Techniques for designing efficient and accurate ML.DL models in distributed environment that can deal with the increasing amounts of available digital data . 7. Case studies and projects in big data processing

Peculiarities of social datafication (what does datafication mean in the society, in the organisations and on the individual level); what kind of data and how could be used on behalf of organisation or community (including developments related to 'data activism'), what interpretational issues should be taken into account, when encountering analysis using large-scale data (paradigm shifts, sample representativeness issues, privacy and ethics, challenges to methods and analysis techniques, examples about the implementation, e.g. social network analysis, mobile positioning, social media and measuring opinions, register data, etc).

The course gives an overview of the techniques of big data analysis in biogeochemical cycles at ecosystem and landscape level (e.g. data analysis derived from eddy covariance method used for greenhouse gas investigations, analysis of data from modern techniques used for the investigations of microorganisms controlling carbon and nutrient cycling in soils), and includes several hands-on exercises. The course provides students with skills necessary to investigate patterns of biogeochemical cycles of ecosystems and landscapes.