• EQF Home Page Icon

Learning Opportunity: Applied Informatics

Applied Informatics

Course Information

Objective(s) of a study programme:

The aim of the Applied Informatics study programme is to prepare high level information technology (IT) professionals being able to use the acquired knowledge, to gain new knowledge via self-education, to predict new tendencies in technology development, to adequately select and apply strategically important technologies and platforms, and also to participate in scientific research and enter doctoral studies in Lithuanian and foreign universities and scientific organizations.
Learning outcomes:

Knowledge and understanding of data mining techniques and their applicability in different domains.
Knowledge and understanding of the design and implementation of intelligent and adaptive systems.
Knowledge of professional development of commercial and social IT products using modern computer platforms, and estimation of their demand, impact and relevance to users, enterprises or organizations.
Ability to perform interdisciplinary R&D in data mining and data analysis field, apply research results in practical applications.
Ability to perform interdisciplinary R&D in natural language processing and information retrieval field, apply research results in practical applications.
Ability to perform interdisciplinary R&D in systems analysis, modelling, identification and control field, apply research results in practical applications.
Ability to apply data mining techniques for the analysis of diverse data (sound, ECG, EEG).
Ability to analyze, formalize and model systems and processes of different complexity.
Ability to apply Natural Language Processing techniques.
Ability to apply parallel programming skills for the development of concurrent distributed and multi-core/-processor systems.
Ability to design multiplatform services and applications, integrating intelligent and adaptive technologies.
Ability to clearly and convincingly present problems and suggested solutions to experts and non-experts, using ground knowledge, reasoning, relevant presentation tools and methods.
Ability to professionally communicate and collaborate in distributed IT projects.
Ability to critically analyse IT projects and their influence to business, culture and society context.
Activities of teaching and learning:

Lectures, seminars, laboratory work, individual work, literature reading, teamwork, problem solving, preparation for laboratory work, midterm exam and final exam.
Methods of assessment of learning achievements:
 Knowledge and skills are evaluated using accumulate criteria-based 10-mark scale study achievement assessment system. Study results are evaluated in the course of semester (mid-term exams, practical, laboratory work) and the final exam. Mid-term exam and final exam are performed in written form. Final evaluation is the sum of weighted marks for each assessment.
Framework:
Study subjects (modules), practical training:

Main study subjects are: System Analysis and Simulation, Machine Learning, Operations Research and Management, Signal Processing and Recognition, Neural Networks, Adaptive and Intelligent Systems, Formal Methods in Modelling, Distributed and Parallel Computing, Mobile Application Infrastructure.
Specialisations:

-
Optional courses:

It is possible:
  to deepen subject areas knowledge, choosing a specialized field of study subjects; to choose a variety of related studies offered by university; to choose free additional general subjects.
  

Distinctive features of a study programme:
Programme is oriented towards today’s and tomorrow’s application domains, covering data retrieval, robotics, artificial intelligence, neural networks, data visualisation, distributed and cloud computing.

Reference Data

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

Minimum education - Higher education

Credits: 

120

Provider Information

Provider Name: 
Vytautas Magnus University
Provider Type: 
University
Provider Contact Info: 

Provider phone number: +370-37-222739 Provider email: info@vdu.lt Provider URL: http://www.vdu.lt

Qualifications Awarded

Reference Data

Qualification Awarded:
Master of Applied informatics
Awarding body:

Vytautas Magnus University

Awarding body contact info:

Provider phone number: +370-37-222739 Provider email: info@vdu.lt Provider URL: http://www.vdu.lt

Course Locations

Reference Data

Course address:

Kauno m. sav. Kauno m. K. Donelaičio g. 58