Artificial Intelligence Technologies
Faculty of information Technology
Name
Artificial Intelligence Technologies
Program code
21443
Qualification awarded
Master Computer Science
Length of programme
2 years
Number of credits
120
level of qualification according to the National Qualification Framework and the European Qualifications Framework
7
Qualification level
Second (Master)
Discipline
Information technologies
Speciality
KnowledgeField EN
Specific admission requirements
First cycle of higher education (NQF Level 6) or higher.
Specific arrangements for recognition of prior learning
Admission was based on the results of the foreign language common entrance examination and a professional examination
Qualification requirements and regulations, including graduation requirements
Programme learning outcomes
Apply methodological principles of scientific research; work with a disciplinary array of publications: search, accumulate and process scientific information; choose and formulate a research problem; choose the methodological basis of the study; formulate the object and the subject of research; formulate and test scientific hypotheses; form a set of methods to study the selected subject; collect empirical data; process and interpret empirical data.
Display the results of scientific research, make scientific reports; participate in scientific discussions; be able to summarize references; present the results of research at scientific conferences and seminars.
Have the skills to qualify the results of creative activities, protect property and personal non-property rights of authors and owners both in Ukraine and abroad; correctly determine the facts of infringement of intellectual property rights and demand appropriate compensation for damages; enter into contracts with the customer or employer; cooperate with collective copyright administrations; register the intellectual property rights; to file a claim regarding infringed intellectual property rights; to protect infringed intellectual property rights in civil law.
Define the subject and object of professional ethics; reveal the basic ethical provisions that are important for professional activities in the field of computer science, consider professional ethics as a way to regulate behavior in specific types of professional activities. Define general principles of professional ethics, such as professional duty and special form of responsibility, professional solidarity and corporatism. Analyze the specifics and types of professional ethics in higher education. Reveal the essence of professional deontology and moral codes.
Apply knowledge of the general principles of didactics, pedagogy, psychology, theory of education from the standpoint of humanization, democratization, national and multicultural orientation of the pedagogical process in higher education.
Form of study
Full-time form
Examination regulations and grading scale
The final evaluation of learning outcomes at the University is carried out on a single 100-point scale. The assessment of the applicant corresponds to the ratio established of the level of professional and general competencies to the planned learning outcomes (as a percentage). The minimum positive level of assessment is 60 points. According to the results of exams, according to the results of course and diploma works (projects); based on the results of work in practice, the student is also graded on a 4-point scale: “Excellent”, “Good”, “Satisfactory”, “Unsatisfactory”. If the final exam is not conducted in the disciplines, the results of the applicant’s work are evaluated on a 2-point scale: “Passed” or “Fail”.
Оbligatory or optional mobility windows (if applicable)
Work placement
Work-based learning
Director of the course
Faculty of information Technology
Occupational profiles of graduates
Computer Systems Analyst,
University Lecturer,
Junior Researcher (Computing Systems)
Access to further studies
Access to programmes of the Third Cycle of Higher Education. Has the right to acquire additional qualifications in the adult education system.
Subjects
As part of the curriculum, students study the following disciplines
Technologies of computational intelligence
Code: ОК.6,
Business Analytics
Code: ДВС.1.02,
«Big Data Analysis, Processing, Storage and Visualization.»
Code: ОК9,
Workshop on research aspects of artificial intelligence
Code: ОК 5,
Multiagent Systems and Technologies
Code: ОК 11,
Modeling and Visualization of Multidimensional Data
Code: ННД 1.08,
Scientific research practice
Code: ОК 15,
Course work on artificial intelligence technologies
Code: ОК14,
Graduation qualification work
Code: ОК16,
Methods of optimization and metaheuristics
Code: ОК 13,