Subject

Design of Algorithms

Course Title

Design of Algorithms
Algorithm design

Code

F23L2S097

Study Programme

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Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

First Cycle

Academic year / semester

4 / Summer

Number of ECTS credits

Teacher

Maria Mihova

Prerequisites for enrolling in the course

Discrete Mathematics or Discrete Structures 2 or Mathematics 2 or Selected Topics in Mathematics

10.

Objectives of the course programme (competences)

In this course, students will learn various algorithms and methods for solving problems with a computer, as well as certain data structures for their implementation. The student will gain programming experience, understand the principles of algorithm design and performance analysis, and learn the fundamental ideas for designing an efficient algorithm and combining it with an appropriate data structure. These ideas will be applied in practice through laboratory exercises.

11.

Course content

What is an algorithm. Techniques for designing algorithms and techniques for calculating complexity. Multidimensional dynamic and greedy programming. Memoization in DP. Graph search (classification of edges and vertices, visit time, and their associated properties). Algorithms for shortest paths from any to any vertex and their applications. Algorithms that use traversal techniques. Union-find, Fibonacci heap, and other advanced structures and primitives. Network flow and min-cut/max-flow. Search trees (segment, interval index). String pattern matching algorithms. Geometric algorithms.

12.

Learning methods

Lectures supported by slide presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lecturers, independent completion of homework assignments, and learning in an electronic environment (forums, consultations).

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	30 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	45 hours

16.

Other forms of activities

16.1.	Project assignments	15 hours
16.2.	Independent assignments	15 hours
16.3.	Home study	75 hours

17.

Assessment method

17.1.	Tests	10 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activities and learning	10 points
17.4.	Final exam	70 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

completed activities 15.1 and 15.2

20.

Language of instruction

Macedonian and English

21.

Method for monitoring the quality of teaching

internal evaluation and survey mechanism

22.

Literature

22.1.	Required literature 1. Thomas H. Carmen et al. \| Introduction to Algorithms \| MIT Press \| 2009 2. Jon Cleindberg, Eva Targos \| Algorithm design \| Pearson Education, Inc \| 2006 3. Maria Mihova, Bojan Ilijoski \| Design of Algorithms from Dynamic Programming \| UCM \| 2019 4. codefu.mk 5. www.topcoder.com 6. http://mendo.mk/Welcome.do
22.2.	Additional literature No. Author Title Publisher Year