Advanced algorithms

Advanced algorithms

1.

Subject title

Advanced algorithms

Напредни алгоритми

2.

Code

KN-Z-01

3.

Study program

Computer Science, Data science in computer science and engineering, IT management, Bioinformatics, Security, Cryptography and Coding, Cloud Computing, Еducation with ICT, Eco-informatics, Inteligent Systems, Internet Technologies and cyber security, Software for embedded systems, Software Engineering, Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Software Engineering, Statistics and Data Analytics, Statistics and Data Analytics,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Зимски

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Ана Мадевска Богданова проф. д-р Марија Михова проф. д-р Миле Јованов

9.

Prerequisites for enrollment

10.

Subject goals and competencies:


The purpose of the subject is to process techniques for the design and analysis of efficient algorithms, especially the methods that are Useful in practice.

11.

Subject content:


Mathematical methods for calculating the complexity of algorithms. Complexity of algorithms, master theorem. Calculating complexity and proving already known algorithms. Probable algorithms. Damping analysis (aggregate analysis, method of recount method, dynamic tables). Sorting networks, matrix operations, linear programming, work with Polynomials and FFT, algorithms of numbers, comparison of strings, Np completeness, approximate algorithms,

12.

Learning methods:


Предавања, вежби, проекти, семинарски, самостојно решавање на задачи

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

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

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

30 hours

16.

Other forms of activities

16.1.

Project tasks

0 hours

16.2.

Independent tasks

0 hours

16.3.

Homework

0 hours

17.

Grading method

17.1.

Tests

0 points

17.2.

Seminar work / 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.

Condition for signature and taking final exam

реализирани активности 15.1 и 15.2

20.

Language of instruction

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

No.

Author

Title

Publisher

Year

6770

Т.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein

Introduction to Algorithms

The MIT Press

2002

6771

Marcello La Rocca

Advanced Algorithms and Data Structures

Manning publications

2021

22.2.

Additional literature

No.

Author

Title

Publisher

Year