Προβολή πηγαίου κώδικα για τη σελίδα Special Topics in Computer Science (MAE841)

* [[Ειδικά Θέματα Αριθμητικής Ανάλυσης (ΜΑΕ842)|Ελληνική Έκδοση]]
{{Course-UnderGraduate-Top-EN}}

=== 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 Examinations
|
Greek
|-
! Is the Course Offered to Erasmus Students
|
Yes 
|-
! Course Website (URL)
| See [https://ecourse.uoi.gr/ eCourse], the Learning Management System maintained by the University of Ioannina.
|}

=== Learning Outcomes ===

{| class="wikitable"
|-
! 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.
<br/>
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
|
* Search for, analysis and synthesis of data and information, with the use of the necessary technology
* Working independently
* Team work
* Project planning and management.
|}
=== 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 ===
{| class="wikitable"
|-
! Delivery
|
Lectures
|-
! Use of Information and Communications Technology
| Use of projector and interactive board during lectures.
|-
! Teaching Methods
|
{| class="wikitable"
! Activity
! Semester Workload
|-
| Lectures
| 39
|-
| Working independently
| 78
|-
| Exercises-Homeworks
| 33
|-
| Course total 
| 150
|}
|-
! Student Performance Evaluation
|
* Final written examination (70%)
* Exercises / Homework (30%)
|}
=== Attached Bibliography ===

<!-- In order to edit the bibliography, visit the webpage -->
<!-- https://wiki.math.uoi.gr/index.php/%CE%A0%CF%81%CF%8C%CF%84%CF%85%CF%80%CE%BF:MAE841-Biblio -->

See the official [https://service.eudoxus.gr/public/departments#20 Eudoxus site] or the [https://cloud.math.uoi.gr/index.php/s/62t8WPCwEXJK7oL local repository] of Eudoxus lists per academic year, which is maintained by the Department of Mathematics. Books and other resources, not provided by Eudoxus:

{{MAE841-Biblio}}