The data association algorithm for the formation of optional IT-courses list system Andrii Roskladka 1[0000-0002-1297-377X] , Nataliia Roskladka 1[0000-0001-7333-4050] Ganna Kharlamova 2[0000-0003-3614-712X] and Andriy Stavytskyy [0000-0002-5645-6758] 1 Kyiv National University of Trade and Economics, Kyoto st. 19, 02156, Kyiv, Ukraine a.roskladka@knute.edu.ua, n.roskladka@knute.edu.ua 2 Taras Shevchenko National University of Kyiv, Vasylkivska st. 90A, 03022, Kyiv, Ukraine akharlamova@ukr.net Abstract. The article contains a study of the principles of student's educational trajectory formation by using modern technologies in data analysis. There is a mandatory requirement to have the selective component (optional to a student) among the curriculum educational components. This rule is legislated in the laws «On Education» and «On Higher Education» of Ukraine as well as in the normative documents on accreditation of educational programs, defined by the Standards and recommendations on quality assurance in the European Space of Higher Education (ESG) and the National Agency for Quality Assurance of Higher Education. However, adherence to the principles of the individual edu- cational trajectory formation is mostly formal and is reduced to offering stu- dents a non-coherent list of courses. On the one hand, this leads to the disorien- tation of a student, who cannot see the systemic perspective of his future pro- fession in the initial list of study courses, and therefore cannot consciously choose the optimal set of optional courses. On the other hand, the unknown choice of courses by students leads to situational management of the education- al process at the HEI. A large number of courses create significant difficulties in managing the selection process. To analyse the process of individual educa- tional trajectory formation, the authors propose to use methods of data associa- tion and, in particular, the apriori algorithm for the formation of associative rules. The procedure of popular sets of elective courses formation, the configu- ration of associative rules of educational courses choice is studied. The charac- teristics of these rules quality are calculated. The example of the procedure im- plementation in analytical platform Deductor Studio is considered. Keywords: individual educational trajectory, selective study courses, Data Sci- ence, data association, associative rules, apriori algorithm. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).