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Learning Opportunity: Informatics


Course Information

Objective(s) of a study programme:
The main objectives of the programme are to educate holders of Master’s degree in Informatics able to carry out analytical research and to apply their results in design and development of distributed software systems; to apply the theories of informatics, new technologies of systems design and modelling; to work as a member or a leader of a group in software design, implementation and development; to compete in Lithuania and abroad.
Learning outcomes:
Knowledge and its application:
Knowing the methods of analysis and synthesis of systems as well as ability to apply them.
Ability to verify the correctness of hypotheses leaning on the theory, analysis of models and experiments.
Knowledge of network systems design.
Ability to apply parallel algorithms and systems.
Ability to maintain data safety and systems security.
Knowing the technologies of data retrieval and data management.
Ability to use technologies for process design and modelling.
Ability to use innovative theories and technologies in informatics.
Will know modern computer architecture and their network models.
Abilities to conduct research:
Knowing the methods of research and reliability as well as the ability to apply them.
Ability to formulate hypotheses on the ground of mathematical, statistical and analytical methods.
Ability to analyse the data, to retrieve new reliable data, to formulate generalisations and make reasoned solutions.
Ability to independently manage applied methods of data analysis and retrieval.
Subject–specific skills:
Ability to assess the effectiveness of algorithms and to apply contemporary methods of optimizations and algorithms.
Ability to analyse, specify, design and implement software systems.
Ability to relate fundamental knowledge to particular requirements of mathematical and software systems projects from various fields.
Ability to evaluate quality parameters of distributed systems, their demand on the market and impact on development of the society.
Ability to create algorithms for networks and data safety.
Social skills:
Ability to consecutively and reasonably present ideas and results of the analytical research or applied work in public.
Ability to apply analytical methods to solve problems.
Ability to work in software development and implementation group and to organise the work of a group.
Personal skills:
Ability to plan work time.
Perception of the importance of continuous professional lifelong learning and will implement it.
Ability to critically assess results of own work.
Activities of teaching and learning:
Lectures, practice, individual work, laboratory works, studying methodical literature, analysing scientific literature, seminars, development of applications, preparing and presenting the literature review, scientific research, preparing the final thesis.
Methods of assessment of learning achievements:
The system of ten-point criteria scale and cumulative assessment system are applied to assess knowledge and abilities. Learning achievements are evaluated during the semester through the intermediate task completions (the colloquiums are conducted, the laboratory works are defended, group and individual works are presented). The tasks of the semester’s individual work are evaluated by grade; the final grade is calculated during the session while multiplying particular grades by a weight coefficient and summing the products. Research work is evaluated during scientific seminars. Exams are performed in a written or a written and oral form.
Study subjects (modules), practical training:
The volume of the subjects of major study field is 108 credits.
The main study subjects are the following: Statistical Modelling and Analysis, Data Management Technologies, Concurrent Programming, Modern Computer Architecture, Technologies of Object-Oriented Design, Data Mining, Methodology of Scientific Research, Modelling of Control Processes, Network Software Design, Modern Algorithms in Cryptography.
Optional courses:
The students can deepen their knowledge in the study field by choosing the specialized subjects of study field: Stochastic Programming, Mathematical Network Models, Computer Modelling of Transfer Phenomena, Design of Internet Applications, Investigation and Applications of Heuristic Algorithms.
Distinctive features of a study programme:

Reference Data

Education Level:
Thematic area:
Teaching Language:
Study Type:
Access requirements: 

Minimum education - Higher education university type



Provider Information

Provider Name: 
Siauliai University
Provider Type: 
Provider Contact Info: 

Provider phone number: +370-41-595800 Provider email: all@cr.su.lt Provider URL: http://www.su.lt

Qualifications Awarded

Reference Data

Qualification Awarded:
Master of Informatics
Awarding body:

Siauliai University

Awarding body contact info:

Provider phone number: +370-41-595800 Provider email: all@cr.su.lt Provider URL: http://www.su.lt

Course Locations

Reference Data

Course address:

Vilniaus g. 88, Šiauliai