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Artificial intelligence

Language of instruction

english, lithuanian

Qualification degree and (or) qualification to be awarded

Bachelor of Computing

Place of delivery

Kaunas, K. Donelaičio g. 73, LT-44249

Institution that has carried out assessment

Studijų kokybės vertinimo centras

Institution that has performed accreditation, accreditation term

Studijų kokybės vertinimo centras, 12/31/2024

Data provided or updated (date)

9/16/2021

Order on accreditation

SV2-6
More about programme

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Summary of the Profile

General Description:
Objective(s) of a study programme:
To provide competences necessary to develop artificial intelligence (AI) based computational systems, which replicate human-made decisions with a particular emphasis on algorithms for data processing and analysis, machine learning, image and speech recognition, social and economic aspects of AI application.
Learning outcomes:
Knowledge and its application:
A1. Is able to explain fundamentals in mathematics, physics, cognitive neuroscience and understand of their relations to research and application of artificial intelligence.
A2. Is able to explain in detail fundamentals in design and analysis of algorithms, programming languages and technologies, software life cycle and engineering processes, to apply them in software development.
A3. Is able to consistently explain basic operational processes and limitations of up-to-date hardware and software, main architectures of computer networks, fundamentals of secure network communication.
A4. Is able to consistently explain concepts, methods and practical applications of system modelling, data collection and analysis.
A5. Is able to consistently explain artificial intelligence processes including expert systems, rule-based and logic-based systems and machine learning.
A6. Is able to consistently explain algorithms of speech and image recognition, identification and segmentation, to determine their fields of applications.
A7. Is able to describe overall digitization processes, evolution of informatics and artificial intelligence, foresee possible tendencies in future applications of artificial intelligence.
A8. Is able to consistently explain ethics guidelines in artificial intelligence, legal requirements including data protection, rights of intellectual property, product safety problems and rules of professional ethics, and understanding how to design trustworthy human-oriented artificial intelligence systems.
A9. Is able to evaluate influence of the changing context in business, technology, social and legal sectors on the artificial intelligence technologies and vice versa.

Research skills:
B1. Is able to perform analysis for input and output data of the system.
B2. Is able to design imitational model of a system, select fundamental processes, validate and verify the model.
B3. Is able to evaluate efficiency of an algorithm in the intelligence systems, perform a comparative analysis of several algorithms.
Special skills:
C1. Is able to choose and construct system architecture of proper parameters to implement artificial intelligence solution.
C2. Is able to create conceptual and graphical models of entities and processes for the analysed system and to select suitable tools and platforms for model development.
C3. Is able to explain optimization theory and to choose appropriate optimization algorithms to solve specific practical engineering problems.
C4. Is able to design hybrid intelligence solutions by applying algorithms of image and speech processing and machine learning.
C5. is able to deliver software life cycle phases by specifying the requirements, designing, developing, testing and implementing the artificial intelligence solutions, including guaranteeing their quality and reliability.
C6. Is able to apply programming and other practical skills while developing autonomous, self-learning and human-assistance intelligence systems.

Social skills:
D1. Is able to present ideas and decisions in written and oral form for various audiences and to communicate in at least one foreign language.
D2. Is able to work in a team as a team member and as a leader.

Personal skills:
E1. Is able to organize work, show initiative and personal responsibility.
E2. Is able to plan self-education, study independently and adopt lifelong learning.
E3. Is able to demonstrate creativity in solving professional tasks and problems.
Activities of teaching and learning:
Lectures, assignments, Laboratory classes, Seminars, Tutorials, Case analysis (Case study), Engineering projects, Team project, Individual project, Design thinking, Creativity workshops, Practice
Methods of assessment of learning achievements:
Examination, Colloquium, Control work, Laboratory examination, Laboratory notes and report, Project report, Report of final practice, Final degree project.
Framework:
Study subjects (modules), practical training:
Mathematics; Object-Oriented Programming; Software Engineering; Databases; Design and Analysis of Computer Algorithms; Data processing and analysis; Algorithms of Machine Learning; Deep Learning; Image Processing and Recognition; Algorithms for Speech Recognition; Fundamentals of Multi-Agent Systems; Intelligent Technologies for Assistance Systems; Robot Programming Technologies; Artificial Intelligence in Computer Games.
Specialisations:
No specialisations.
Optional courses:
During the studies student can choose:
Study field subject (6 ECTS credits) from suggested 3 electives (Intelligent Technologies for Assistance Systems, Artificial Intelligence in Computer Games, Robot Programming Technologies).
Subject (6 ECTS credits) from any field.
Distinctive features of a study programme:
During the first year of studying, students deepen their knowledge in programming technologies, designing and analyzing algorithms, fundamentals of software engineering, designing and modelling IT systems. That is, students get knowledge which is necessary for IT specialist of any field and increase their general competences as a developer of software systems and designer of solutions in informatics. Since the second year, students study topics on artificial intelligence, such as data processing and analysis, image processing and analysis, machine learning algorithms, deep learning. They also learn to design and develop AI-based solutions and systems.
While studying, students have opportunity to gain practical experience in leading Lithuanian and foreign companies which implement solutions in software engineering, information technology and artificial intelligence fields.
Access to professional activity or further study:
Access to professional activity:
A graduate can work as AI Solutions Architect, AI Analyst, Intelligence Systems Developer, IT Systems Developer, Developer of Assistance Systems, Intelligence Systems Maintainer.
Access to further study:
The study programme has continuity in all three study cycles (Bachelor’s, Master’s, Doctorate). After graduating the programme, AI specialist has access to the second cycle studies of Informatics, Software Engineering or Information and Information Technology Security. For those who plan to continue studies in the third cycle (Doctorate), the PHD programmes of Informatics and Informatics Engineering are offered at the University.