Special Topics in Computer Science (ΠΛ10): Διαφορά μεταξύ των αναθεωρήσεων
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=== General === | === General === | ||
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! Learning outcomes | ! Learning outcomes | ||
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* The aim of the course is to specialize in areas covered by Computer Science in applied fields. It provides background in data and information management. The specialization covers cognitive domains such as Databases, Machine Learning, Artificial Intelligence, Data Mining, etc. It also addresses all issues related to the design and optimization of computer hardware and software. This includes cognitive areas such as Programming Languages and their Implementation, Compilers, Hardware Design, Computer Architecture, Operating Systems, Distributed Systems, and more. | |||
* The students of the course are expected to deepen in modern data processing techniques both theoretically and practically, while also acquiring a multifaceted knowledge of the principles of computer system design and programming. | |||
* The course includes individual exercises, summary writing projects and presentation of relevant research papers. | |||
* The material will be adapted and specialized according to the necessary developments and requirements. | |||
|- | |- | ||
! General Competences | ! General Competences | ||
| | | | ||
* Search for, analysis and synthesis of data and information, with the use of the necessary technology | |||
* Working independently | |||
* Team work | |||
* Project planning and management | |||
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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 | ||
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Lectures | |||
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! Use of Information and Communications Technology | ! Use of Information and Communications Technology | ||
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Use of projector and interactive board during lectures. | |||
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! Teaching Methods | ! Teaching Methods | ||
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| 39 | | 39 | ||
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| | | Working independently | ||
| | | 78 | ||
|- | |- | ||
| | | Exercises - Homework | ||
| | | 70.5 | ||
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| Course total | | Course total | ||
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! Student Performance Evaluation | ! Student Performance Evaluation | ||
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* Written exercises (50%) | |||
* Essay / report (20%) | |||
* Public presentation (30%) | |||
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Τελευταία αναθεώρηση της 05:17, 16 Ιουνίου 2023
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General
| School | School of Science |
|---|---|
| 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 |
|
|---|---|
| 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.