Προβολή πηγαίου κώδικα για τη σελίδα Design and Analysis of Algorithms (MAE581)

* [[Σχεδίαση και Ανάλυση Αλγορίθμων (ΜΑΕ581)|Ελληνική Έκδοση]]
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=== General ===
{| class="wikitable"
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! School
|
School of Science
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! Academic Unit
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Department of Mathematics
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! Level of Studies
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Undergraduate
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! Course Code
|
MAE581
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! Semester
|
5
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! Course Title
|
Design and Analysis of Algorithms
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! Independent Teaching Activities
|
Lectures, laboratory exercises, tutorials, quiz (Weekly Teaching Hours: 3, Credits: 6)
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! Course Type
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Special Background
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! Prerequisite Courses
| -
|-
! Language of Instruction and Examinations
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Greek
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! 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"
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! Learning outcomes
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This course aims at introducing to students the philosophy of fundamental algorithmic background and techniques. After successfully passing this course the students will be able to:
* Understand basic algorithmic techniques 
* Analyze complex algorithms 
* Design new algorithmic tools
* Combine already-known techniques for solving new algorithmic problems 
|-
! General Competences
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* 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 ===
* Fundamental concepts of design and analysis of algorithms
* Analysis of algorithms, Asymptotical growing functions
* Typical running times and data structures  (lists, arrays, queues, stacks)
* Stable matching, correctness, priority queue
* «Divide & Conquer» technique, sorting, recursive formulations
* Graph algorithms: BFS, DFS, connectedness, topological ordering
* Greedy algorithms: interval scheduling & shortest paths (Dijkstra)
* Minimum spanning trees(Prim & Kruskal algorithms), Huffman coding
* Dynamic programming: maximum flow, interval scheduling, and Knapsack
* Further Topics: computational complexity and ΝΡ-completeness.
=== Teaching and Learning Methods - Evaluation ===
{| class="wikitable"
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! Delivery
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Lectures
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! Use of Information and Communications Technology
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* Use of projector and interactive board during lectures.
* Course website maintenance. Announcements and posting of teaching material (lecture slides and notes, programs).
* Announcement of assessment marks via the ecourse platform by UOI.
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! Teaching Methods
|
{| class="wikitable"
! Activity
! Semester Workload
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| Lectures
| 39
|-
| Working independently
| 78
|-
| Team work
| 33
|-
| Course total 
| 150
|}
|-
! Student Performance Evaluation
|
Final written examination (70%)
* Design and analyze algorithms
Exercises (30%)
* Design and analyze algorithms
|}

=== Attached Bibliography ===

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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:

{{MAE581-Biblio}}