Artificial Intelligence
Faculty of Computer Science and Cybernetics
Name
Artificial Intelligence
Program code
122
Qualification awarded
Master
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
Bachelor's degree
Specific arrangements for recognition of prior learning
Qualification requirements and regulations, including graduation requirements
Programme learning outcomes
Form of study
Distance form
Examination regulations and grading scale
In accordance with the requirements of the "Regulations on the organization of the educational process at the Taras Shevchenko National University of Kyiv".
http://nmc.univ.kiev.ua/docs/poloz_org_osv_proc-2018.pdf
Оbligatory or optional mobility windows (if applicable)
Work placement
Production practice can be conducted both on the basis of the graduating department and on the basis of enterprises, organizations, research institutes, banks, insurance companies and other institutions engaged in the design, development, implementation and operation of automated information systems. The choice of practice bases is carried out in coordination with the graduating department, taking into account the tasks of practice and the possibility of their implementation. In particular, the following organizations can act as production practice bases: Samsung, GlobalLogic, Avora, EPAM, SoftServ, InfoPulse, DataArt and others.
Work-based learning
-
Director of the course
Iurii
V
Krak
Theoretical Cybernetics
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Occupational profiles of graduates
Access to further studies
Getting education under the educational program of the third (educational-scientific) level of higher education and getting additional qualifications in the adult education system.
Subjects
As part of the curriculum, students study the following disciplines
Information security
Code: ННД.04,
Formal methods in software development
Code: ННД.07 ,
Neural Networks
Code: ДВС.1.03,
Logic and automated deduction
Code: ННД.18 ,
Image Analysis Computer Vision
Code: ННД.17.,
/ Convolutional Neural Networks for Visual Recognition
Code: ДВС.2.05,
Compositional logics
Code: ОК.09,
Data Mining Actual Problem
Code: ОК.13,