Advanced mathematical and statistical techniques

1.

Subject title

Advanced mathematical and statistical techniques

Напредни математички и статистички техники

2.

Code

BI-Z-03

3.

Study program

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

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Георгина Мирчева проф. д-р Соња Гиевска

9.

Prerequisites for enrollment

10.

Subject goals and competencies:

The student will be capable of using mathematical techniques for modeling and analyzing biological systems.

11.

Subject content:

This subject covers the methods of statistical inference and stochastic modeling with the application of functional genomic and computational molecular biology. Calculations will be applied by using data from biological databases. The structure of the subject will include: Statistical theory of Sequence Analysis and Database Search, Markets Models and Hidden Marks, Baes`s Elements and Inference of similarity, discreet data models, application of linear regression analysis, multivariate data analysis methods (RSA, clustering), software tools for statistical calculations. Applying Deep Learning Advanced Techniques (Graf Neuroscience, General Contrast Networks, Learning Transfer) to detect knowledge in biomedical and bionformatic data.

12.

Learning methods:

Предавања поддржани со презентации преку слајдови, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача и семинарска работа, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

60 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

0 hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

15 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

15 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

20.

Language of instruction

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature