Subject

Advanced Algorithms

Course Title

Advanced Algorithms
Advanced algorithms

Code

KN-Z-01

Study Programme

Computer Science

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

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

Second cycle

Academic year / semester

9 / Winter

Number of ECTS credits

Teacher

Ana Madevska Bogdanova, Marija Mihova, Mile Jovanov

Prerequisites for enrolling in the course

—

10.

Objectives of the course programme (competences)

The objective of the course is to cover techniques for designing and analyzing efficient algorithms, especially methods that are
useful in practice.

11.

Course content

Mathematical methods for calculating algorithm complexity. Algorithm complexity, master theorem. Calculating complexity and proving already known algorithms.
Probabilistic algorithms.
Amortized analysis (aggregate analysis, accounting method, potential method, dynamic tables).
Sorting networks, matrix operations, linear programming, working with
polynomials and FFT, number-theoretic algorithms, string matching,
NP-completeness, approximation algorithms,

12.

Learning methods

Lectures, exercises, projects, seminar papers, independent problem solving

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

30 + 30 + 0 + 0 + 0 = 180 hours

15.

Forms of teaching activities

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

16.

Other forms of activities

16.1.	Project assignments	0 hours
16.2.	Independent assignments	0 hours
16.3.	Home study	0 hours

17.

Assessment method

17.1.	Tests	0 points
17.2.	Seminar paper / project (presentation: written and oral)	0 points
17.3.	Activities and learning	0 points
17.4.	Final exam	0 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. T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein \| Introduction to Algorithms \| The MIT Press \| 2002 2. Marcello La Rocca \| Advanced Algorithms and Data Structures \| Manning publications \| 2021
22.2.	Additional literature No. Author Title Publisher Year