Entry to specialty
Course: Data science
Structural unit: Faculty of information Technology
Title
Entry to specialty
Code
ОК 30
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
1 Semester
Number of ECTS credits allocated
2
Learning outcomes
Apply knowledge of the basic forms and laws of abstract and logical thinking, the basics of the methodology of scientific knowledge, the forms and methods of extracting, analyzing, processing and synthesizing information in the subject area of computer science. Use the methodology of system analysis of objects, processes and systems for the tasks of analysis, forecasting, management and design of dynamic processes in macroeconomic, technical, technological and financial objects. Apply methods and algorithms of computational intelligence and intelligent data analysis in the tasks of classification, forecasting, cluster analysis, finding associative rules using software tools to support multidimensional data analysis based on DataMining, TextMining, WebMining technologies.
Form of study
Full-time form
Prerequisites and co-requisites
There are no prerequisites
Course content
The purpose of the discipline is to acquaint first-year students with the specialty "Computer Science" with general issues of the standard of higher education in Ukraine; familiarization with the educational and qualification characteristics and the educational and professional training program of a computer science specialist; familiarization with the organization of specialist training at Taras Shevchenko Kyiv National University. Students are introduced to the professional requirements for a specialist, familiarization with the list of positions that a computer science specialist can hold, features of the " Data analytics" educational program. Acquaintance with the curriculum, with the organization of educational, research and independent work of students. An overview of the main directions of computer science, modern information technologies, types of their support, basic issues of artificial intelligence and data analytics. Introduction to the organization of work on the creation of a software product.
Recommended or required reading and other learning resources/tools
Planned learning activities and teaching methods
Lectures, practical activities, individual work
Assessment methods and criteria
Assessment of students is carried out throughout the semester for all types of work, including independent work and the completion of an essay. During the semester, after the completion of the relevant topics, an oral survey of students is conducted based on the material covered, and a summary of practical classes is conducted. The credit is issued to the student based on the results of the work during the semester. Upon receiving the resulting final number of points from 60 and above, the student is assigned a credit. Students who scored a total of less points than the critical calculation minimum - 40 points are not allowed to pass the test. The recommended minimum for admission to the test is 48 points.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline