Special Topics in Computer Science (ΠΛ10): Διαφορά μεταξύ των αναθεωρήσεων
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=== General === | === General === | ||
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=== Syllabus === | === Syllabus === | ||
The main objective of the course is to specialize in areas covered by Computer Science in applied fields such as: | |||
* Data Mining | |||
* Artificial Intelligence | |||
* Database Systems | |||
* Security of Information Systems | |||
* Distributed Systems | |||
* Mobile and Wireless Networks | |||
* Pattern Recognition | |||
* Machine Learning | |||
* Signal Processing | |||
The specialized subject will be adapted and specialized according to the necessary developments and requirements. | |||
=== Teaching and Learning Methods - Evaluation === | === Teaching and Learning Methods - Evaluation === | ||
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! Delivery | ! Delivery | ||
| | | | ||
Lectures | |||
|- | |- | ||
! Use of Information and Communications Technology | ! Use of Information and Communications Technology | ||
| | | | ||
Use of projector and interactive board during lectures. | |||
|- | |- | ||
! Teaching Methods | ! Teaching Methods | ||
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| 39 | | 39 | ||
|- | |- | ||
| | | Working independently | ||
| | | 78 | ||
|- | |- | ||
| | | Exercises - Homework | ||
| | | 70.5 | ||
|- | |- | ||
| Course total | | Course total | ||
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! Student Performance Evaluation | ! Student Performance Evaluation | ||
| | | | ||
* Written exercises (50%) | |||
* Essay / report (20%) | |||
* Public presentation (30%) | |||
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Τελευταία αναθεώρηση της 05:17, 16 Ιουνίου 2023
- Ελληνική Έκδοση
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General
School | School of Science |
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Academic Unit | Department of Mathematics |
Level of Studies | Graduate |
Course Code | ΠΛ10 |
Semester | 2 |
Course Title | Special Topics in Computer Science |
Independent Teaching Activities | Lectures (Weekly Teaching Hours: 3, Credits: 7.5) |
Course Type | Elective |
Prerequisite Courses |
641 - Design and Analysis of Algorithms |
Language of Instruction and Examinations |
Greek |
Is the Course Offered to Erasmus Students | Yes (in English) |
Course Website (URL) | See eCourse, the Learning Management System maintained by the University of Ioannina. |
Learning Outcomes
Learning outcomes |
|
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General Competences |
|
Syllabus
The main objective of the course is to specialize in areas covered by Computer Science in applied fields such as:
- Data Mining
- Artificial Intelligence
- Database Systems
- Security of Information Systems
- Distributed Systems
- Mobile and Wireless Networks
- Pattern Recognition
- Machine Learning
- Signal Processing
The specialized subject will be adapted and specialized according to the necessary developments and requirements.
Teaching and Learning Methods - Evaluation
Delivery |
Lectures | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Use of Information and Communications Technology |
Use of projector and interactive board during lectures. | ||||||||||
Teaching Methods |
| ||||||||||
Student Performance Evaluation |
|
Attached Bibliography
- Evans Alan, Martin Kendall, Poatsy Mary Anne, Εισαγωγή στην πληροφορική: Θεωρία και Πράξη, Κωδικός Βιβλίου στον Εύδοξο: 41955480, 2014
- Παπαδόπουλος, Α., Μανωλόπουλος, Ι., Τσίχλας, Κ. 2015. Εισαγωγή στην Ανάκτηση Πληροφορίας, Αποθετήριο «Κάλλιπος», 2015.
- Παρασκευάς, Μιχαήλ, Ειδικά θέματα εφαρμογών της Κοινωνίας της Πληροφορίας, Αποθετήριο «Κάλλιπος», 2015.
- Δημακόπουλος, Β. Εισαγωγή: Παράλληλα Συστήματα και Προγραμματισμός, Αποθετήριο «Κάλλιπος», 2015.