| 1. | Course Title | Advanced Concepts of Data Processing and Storage | |||||||||||
| 2. | Code | 4ФЕИТ07010 | |||||||||||
| 3. | Study program | 7-NKS, 20-IMSA | |||||||||||
| 4. | Organizer of the study program (unit, institute, department) | Faculty of Electrical Engineering and Information Technologies | |||||||||||
| 5. | Degree (first, second, third cycle) | Second cycle | |||||||||||
| 6. | Academic year/semester | I/1 | 7. | Number of ECTS credits | 6.00 | ||||||||
| 8. | Lecturer | Dr Goran Jakimovski | |||||||||||
| 9. | Course Prerequisites | ||||||||||||
| 10. | Course Goals (acquired competencies):
Managing, modeling, storing and mining data. Working with semi-structured and unstructured databases. Working with XML and MySQL and tools and concepts to convert and work with NoSQL. Storing and mining multimedia data. |
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| 11. | Course Syllabus:
Overview of structural databases, pros and cons of standard data structures. Introducing semi-structured databases and concepts of XML. Creating optimal strategy for storing and access to semi-structured data and concepts of unstructured databases. Concepts of NoSQL against SQL. Optimizing data storing and interpretation of data through mining. Different types of data storage, processing and decision making with multimedia data. Incorporating multimedia data with existing data (database). |
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| 12. | Learning methods:
lectures with presentations, homework and project assignment |
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| 13. | Total number of course hours | 180 | |||||||||||
| 14. | Distribution of course hours | 3 + 3 | |||||||||||
| 15. | Forms of teaching | 15.1 | Lectures-theoretical teaching | 45 hours | |||||||||
| 15.2 | Exercises (laboratory, practice classes), seminars, teamwork | 45 hours | |||||||||||
| 16. | Other course activities | 16.1 | Projects, seminar papers | 30 hours | |||||||||
| 16.2 | Individual tasks | 30 hours | |||||||||||
| 16.3 | Homework and self-learning | 30 hours | |||||||||||
| 17. | Grading | ||||||||||||
| 17.1 | Exams | 0 points | |||||||||||
| 17.2 | Seminar work/project (presentation: written and oral) | 50 points | |||||||||||
| 17.3. | Activity and participation | 0 points | |||||||||||
| 17.4. | Final exam | 50 points | |||||||||||
| 18. | Grading criteria (points) | up to 50 points | 5 (five) (F) | ||||||||||
| from 51 to 60 points | 6 (six) (E) | ||||||||||||
| from 61 to 70 points | 7 (seven) (D) | ||||||||||||
| from 71 to 80 points | 8 (eight) (C) | ||||||||||||
| from 81 to 90 points | 9 (nine) (B) | ||||||||||||
| from 91 to 100 points | 10 (ten) (A) | ||||||||||||
| 19. | Conditions for acquiring teacher’s signature and for taking final exam | 60% success in all curricular activities | |||||||||||
| 20. | Forms of assessment | Project assignment and final exam. | |||||||||||
| 21. | Language | Macedonian and English | |||||||||||
| 22. | Method of monitoring of teaching quality | self evaluation | |||||||||||
| 23. | Literature | ||||||||||||
| 23.1. | Required Literature | ||||||||||||
| No. | Author | Title | Publisher | Year | |||||||||
| 1. | Ralph Stair, George Reynolds | Fundamentals of information systems | Course Technology | 2015 | |||||||||
| 2. | Anand Jarajaman, Jerffrey Ullman | Mining of massive datasets | Cambridge | 2011 | |||||||||
| 3. | Eliotte Harold | XML bible, 3rd edition | John Wiley & Sons | 2004 | |||||||||
