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Artificial Intelligence Systems
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Summary of the Profile
General Description:
Objective(s) of a study programme:
To provide the knowledge and skills in informatics and electronic sciences needed to design, develop, apply and maintain artificial intelligence and machine learning systems, to understand their impact on the environment, to develop the ability to creatively and critically solve informatics engineering problems and to maintain professional competence in lifelong learning.
Learning outcomes:
Students will learn:
Z1. Consistently explain the basic facts, concepts, theories, and mathematical methods related to artificial intelligence systems operation, hardware and software, its features and practical applications, communication, and applied solutions related to important historical, current, and potential developments and future trends in the area.
Z2. Consistently explain artificial intelligence systems relevant principles of algorithm design and analysis, programming paradigms, languages and technologies, principles of human-computer interaction, typical stages of the software life cycle, and software development as well as maintenance methods.
Z3. Consistently explain how the business, industrial, economic and social context affects artificial intelligence application areas, defines ethical standards and regulates legal requirements, including data protection, intellectual property rights, contracts, product safety, liability and other related issues.
Z4. Apply the knowledge of informatics and electronic engineering study fields to develop security and other relevant criteria meeting artificial intelligence systems solutions for solving problems of professional activity.
Z5. Consistently explain development methods, structure, operation principles and specific tasks addressing applications of computer and other specialized digital equipment used in artificial intelligence systems.
Students will develop research skills and will be able to:
GT1. In different abstraction levels describe the problem of professional activity in the field of informatics engineering.
GT2. Using effective methods prepare various source data and information required for artificial intelligence systems.
GT3. Using effective methods and according to relevant criteria analyze the data, information and solutions required for artificial intelligence systems.
GT4. Using reasoned conclusions and recommendations, critically evaluate collected and obtained data, information, results and developed solutions.
Students will develop special skills:
SG1. Apply relevant artificial intelligence based methods in informatics and electronic engineering, formulating and solving tasks in various fields.
SG2. Select software and hardware when developing new or improving existing intelligent computer systems.
SG3. Properly implement specialized software for artificial intelligence electronic systems using relevant standards, typical life cycle stages and project management techniques (Artificial Intelligence Electronic Systems Specialization).
SG4. Properly implement specialized software for artificial intelligence program systems, applying relevant standards, typical life cycle stages and project management methods (Artificial Intelligence Software Systems Specialization).
SG5. Evaluate intelligent computer systems according to performance, security and reliability criteria.
SG6. . Plan and properly implement the maintenance and development of artificial intelligence electronic systems (Artificial Intelligence Electronic Systems Specialization).
SG7. Plan and properly implement the maintenance and development of artificial intelligence program systems (Artificial Intelligence Software Systems Specialization).
SG8. Methodically prepare a specification, design, or other documentation required to develop an artificial intelligence based product or service.
Students will develop such social skills:
CG1. Communicate professionally in the state and at least one foreign language with various audiences.
CG2. Work effectively in teams in accordance with the principles and rules of professional, ethical conduct and social responsibility.
Students will develop following personal skills:
AG1. Systematic and self-study learning for continuous personal and professional development.
AG2. Work independently, systematically and responsibly, taking initiative and personal responsibility.
AG3. Demonstrate creativity in solving professional tasks and problems.
Activities of teaching and learning:
Inspiring lectures; laboratory works; individual consultations; seminars, studies in small groups; practical works, solution of problems; practice; individual or group projects; case study; preparation of paper or other writing work; search and generalization of new knowledge; books and articles reading; preparation and presentation of oral presentations; experimentation; discussion.
Methods of assessment of learning achievements:
Writing or oral exam; intermediate exam; control works with open or/and close type problems; homeworks; report and defence of laboratory works; presentation and posters; writing works; report of individual or group project/work/paper; report of practice; final work (project) and its defence; cumulative assessment.
Framework:
Study subjects (modules), practical training:
The volume of the study field subjects of the study program is 156 credits (with practice).
The following core subjects (in the groups of the general theoretical fundamentals and the main subjects of the study field) are studied: Fundamental of Artificial Intelligence; Python Programming; Scripting Programming; Object-Oriented Programming; Algorithms and Data Structures; Computer Architecture; Electronic Devices; Databases; Concepts of Operating System; Software Systems Engineering; Computer Networks; Cloud Computing; Image Recognition Systems; Mechatronic Devices; Machine Learning; Big Data Processing; Fundamentals of Information Security.
The program provides a professional practice, the duration of which is 2 months (15 credits).
Specialisations:
Artificial Intelligence Electronic Systems;
Artificial Intelligence Software Systems
Optional courses:
You can optionally choose up to 66 credits:
a) to deepen knowledge in the field of study by choosing the subjects of the respective specialization (48 credits);
b) to choose three subjects (each 3 credits) from the offered 8 general university education subjects (9 credits);
c) to choose one of the 3 electives in the field of specialization of the Artificial Intelligence Electronic Systems;
d) to choose two subjects (each 3 credits) from the list of optional subjects of the university (6 credits).
Distinctive features of a study programme:
a) the programme focuses on:
• knowledge of the IT and electronic products value chain,
• artificial intelligence technologies,
• development of software and embedded applications,
• interdisciplinary practical work caried in a team and solving the tasks of business enterprises;
b) unique content of the programme:
• enabling to deepen the knowledge in artificial intelligence electronic or software systems specializations;
• strengthening inter-functional understanding, ability to apply SCRUM, or other agile methods in project management, working together with colleagues from other study programmes;
• based not only on the basics of IT and artificial intelligence, but also on knowledge of mechatronics and electronic devices, multimedia systems, digital devices and digital signal processing;
• allowing to discover and delve into the chosen topic – up to 39 credits are allocated for this (15 credits of practice, 9 credits for complex project and 15 credits for the final work focused on the development of an innovative product);
c) experienced teachers:
• constantly evolving and positively valued by students,
• working in pedagogical and practical work on projects,
• conducting research in the development of information electronic systems, optimization of their performance, application of artificial intelligence, virtual reality, multimedia, image and sound signal processing.
Access to professional activity or further study:
Access to professional activity:
Graduates will be able to:
• work as machine learning, deep learning or computer vision engineers, big data architects, business intelligence/analytics developers, artificial intelligence solution implementation and debugging coordinators;
• jobs for artificial intelligence specialists are offered by world-famous companies: Google, Facebook, Amazon, IBM, SkyScanner, Intel, ARM, Samsung, NVIDIA, Keysight, JP Morgans, Citigroup, etc .;
• companies such as „Neurotechnology“, „Baltnetos komunikacijos“, SEB bank, „Swedbank“, „Alna Intelligence“, „Intelektualios technologijos“, „Simplit“, „IT City“, „IT Sistemos“, „Universalios valdymo sistemos“, „Aiva sistema“, „Blue Bridge“, Lithuanian Radio and Television, etc.;
• create new or manage existing IT companies.
Access to further study:
Upon completion of the Artificial Intelligence Systems study programme, studies can be continued in master's study programs in the field of informatics science.
