Introduction to Stochastic Processes

Course title

Code

F18L2S090

Study programme

—

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

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

First cycle

Academic year / semester

4 / Summer

Number of ECTS credits

Teacher

—

Prerequisites for enrolling in the course

Веројатност и статистика или Основи на теорија на информации

10.

Course objectives (competences)

Students will be able for modelling of stochastic processes in real situations.

11.

Course content

Stochastic processes: definition, characteristics, and transformations. Stationary of random processes. Markov chain. Branching processes.
Poisson process. Markov process. Queuing systems. Brownian motion (Winner process).

12.

Learning methods

Mastering concepts, properties, and techniques through independent work; solving assigned tasks and practice problems; completing a project assignment.

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of the available time

30 + 30 + 25 + 15 + 80 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures – theoretical teaching	30 hours
15.2.	Exercises (laboratory, auditory), seminars, team work	30 hours

16.

Other forms of activities

16.1.	Project assignments	15 hours
16.2.	Individual assignments	25 hours
16.3.	Home study	80 hours

17.

Grading

17.1.	Tests	0 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activity and participation	0 points
17.4.	Final exam	75 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.

Requirements for signature and taking the final exam

15.1 and 15.2

20.

Language of instruction

Macedonian and English

21.

Method of monitoring teaching quality

internal evaluation and survey mechanism

22.

Literature