Special Topics in Computer Science (MAE841): Διαφορά μεταξύ των αναθεωρήσεων
(Νέα σελίδα με '=== General === {| class="wikitable" |- ! School | School of Science |- ! Academic Unit | Department of Mathematics |- ! Level of Studies | Undergraduate |- ! Course Code | MAE841 |- ! Semester | 8 |- ! Course Title | Special Topics in Computer Science |- ! Independent Teaching Activities | Lectures, exercises, tutorials (Weekly Teaching Hours: 3, Credits: 6) |- ! Course Type | Special Background |- ! Prerequisite Courses | - |- ! Language of Instruction and Exami...') |
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[[Undergraduate Courses Outlines]] - [https://math.uoi.gr Department of Mathematics] | |||
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Αναθεώρηση της 08:17, 2 Ιουλίου 2022
Undergraduate Courses Outlines - Department of Mathematics
General
School |
School of Science |
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Academic Unit |
Department of Mathematics |
Level of Studies |
Undergraduate |
Course Code |
MAE841 |
Semester |
8 |
Course Title |
Special Topics in Computer Science |
Independent Teaching Activities |
Lectures, exercises, tutorials (Weekly Teaching Hours: 3, Credits: 6) |
Course Type |
Special Background |
Prerequisite Courses | - |
Language of Instruction and Examinations |
Greek |
Is the Course Offered to Erasmus Students |
Yes |
Course Website (URL) | - |
Learning Outcomes
Learning outcomes |
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.
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General Competences |
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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 | ||||||||||
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Use of Information and Communications Technology | Use of projector and interactive board during lectures. | ||||||||||
Teaching Methods |
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Student Performance Evaluation |
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Attached Bibliography
- Evans Alan, Martin Kendall, Poatsy Mary Anne, Introduction to Computer Science: Theory and Practice, Κωδικός Βιβλίου στον Εύδοξο: 41955480, 2014.
- Παπαδόπουλος, Α., Μανωλόπουλος, Ι., Τσίχλας, Κ. 20# Εισαγωγή στην Ανάκτηση Πληροφορίας, Αποθετήριο «Κάλλιπος», 2015.
- Παρασκευάς, Μιχαήλ, Ειδικά θέματα εφαρμογών της Κοινωνίας της Πληροφορίας, Αποθετήριο «Κάλλιπος», 20#
- Δημακόπουλος, Β. Εισαγωγή: Παράλληλα Συστήματα και Προγραμματισμός, Αποθετήριο «Κάλλιπος», 2015.