| Course title | Information and Data Processing |
| Course code | InfTB015 |
| Credit points (ECTS) | 4 |
| Total Hours in Course | 108 |
| Number of hours for lectures | 10 |
| Number of hours for seminars and practical classes | 34 |
| Number of hours for laboratory classes | 0 |
| Independent study hours | 64 |
| Date of course confirmation | 30/09/2024 |
| Responsible Unit | Institute of Computer Systems and Data Science |
| Course developers | |
| Dr. paed., asoc. prof. Nataļja Vronska |
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| There is no prerequisite knowledge required for this course | |
| Course abstract | |
| During the course, students learn how to search for information, develop data collection and presentation skills, as well as develop the ability to analyse and process data. The aim of the course is to provide in-depth knowledge, skills and competences in information resources, databases and software for searching, processing and presenting information. | |
| Learning outcomes and their assessment | |
| Knowledge - knows about automatic document processing, use of spreadsheets in data processing and presentation – practical works.
Skills - analyse, evaluate and systematise information, present and process data using relevant software – 1.-3.test works. Competences - be able to independently select, evaluate information and make decisions using appropriate software or IT – 1.-3.test works. |
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| Course Content(Calendar) | |
| 1.Using, modifying and creating styles. Work in sections (lecture - 2 h, practical work - 3 h).
2.Creation of a table of contents and an index of subjects. Captions and numbering of figures and tables. Creation of table or figures lists (lecture - 1 h, practical work - 4 h). 3.Creating of bookmarks. Creating a bibliography using APA style. Inserting references in a document (lecture - 1 h, practical work - 4 h). 1. test work 4.Spreadsheets: Creating and using complex functions in calculations (lecture - 1 h, practical work - 4 h). 5.Interactive visual analysis of data (lecture - 1 h, practical work - 6 h). 6.Advanced data filter. Forecasting (lecture - 1 h, practical work - 4 h). 2. test work 7.Creating presentations and infographics (lecture - 1 h, practical work - 3 h). 8.Artificial intelligence. Information technology opportunities and potential risks. Electronic information security and data protection (lecture - 1 h, practical work - 1 h) 9.Data warehouses and information sharing (lecture - 1 h, practical work - 2 h). 3. test work |
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| Requirements for awarding credit points | |
| The course includes three test works. Practical works to be done during practical work in the classroom. All work must be successfully completed. | |
| Description of the organization and tasks of students’ independent work | |
| Within the study course, for independent works is given 60 hours. Independent works are organized as follows: preparation for the test works (20 hours for each work). | |
| Criteria for Evaluating Learning Outcomes | |
| The final grade in the study course is formed by:
33.3 % test work about the preparation of large documents; 33.3 % test work about data processing methods and interactive visual data analysis; 33.3 % test work about presentation design, information security, data protection and sharing. |
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| Compulsory reading | |
| • Basham S. Word 2019 in Easy Steps. United Kingdom,
2018, p.307 • Wilson K. Using Excel. Elluminet Press, 2020, p. 149. • Winston W.L. MS Excel 2019. Data Analysis and Business Modeling. 2019, p. 880 |
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| Notes | |
| For full-time and part-time students of the professional bachelor's study program Food Technology. | |