Faculty of Electrical Engineering / / HARDVERSKO-SOFTVERSKI DIZAJN ELEKTRONSKIH KOLA I SISTEMA

Course:

HARDVERSKO-SOFTVERSKI DIZAJN ELEKTRONSKIH KOLA I SISTEMA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12057	Obavezan	3	6	2+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 2 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / IZBORNI PREDMET HEURISTIČKE METODE OPTIMIZACIJE

Course:

IZBORNI PREDMET HEURISTIČKE METODE OPTIMIZACIJE/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12790	Obavezan	2	6	1+0+1

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 1 sat(a) theoretical classes 1 sat(a) practical classes 0 excercises 6 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / TEORIJA INFORMACIJA I KODOVA

Course:

TEORIJA INFORMACIJA I KODOVA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12805	Obavezan	1	5	3+1+0

Programs
Prerequisites
Aims
Learning outcomes	After passing this exam, the student will be able to: - Understand the fundamentals of coding theory, source modeling, and channel modeling. - Know and explain basic codes for entropy coding (Huffman code with variations) and auxiliary codes for source coding. - Know and explain codes for channel coding such as Hamming codes and BCH codes.
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
5 credits x 40/30=6 hours and 40 minuts 3 sat(a) theoretical classes 0 sat(a) practical classes 1 excercises 2 hour(s) i 40 minuts of independent work, including consultations	Classes and final exam: 6 hour(s) i 40 minuts x 16 =106 hour(s) i 40 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 6 hour(s) i 40 minuts x 2 =13 hour(s) i 20 minuts Total workload for the subject: 5 x 30=150 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 30 hour(s) i 0 minuts Workload structure: 106 hour(s) i 40 minuts (cources), 13 hour(s) i 20 minuts (preparation), 30 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / DIZAJN I RAZVOJ SOFTVERA

Course:

DIZAJN I RAZVOJ SOFTVERA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12810	Izborni	2	6	3+0+1

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 1 sat(a) practical classes 0 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / ZAŠTITA I SIGURNOST MULTIMEDIJALNIH I RAČ.PODATAKA

Course:

ZAŠTITA I SIGURNOST MULTIMEDIJALNIH I RAČ.PODATAKA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12814	Obavezan	2	6	1+1+0

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 1 sat(a) theoretical classes 0 sat(a) practical classes 1 excercises 6 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / MATEMATIČKE METODE U RAČUNARSTVU

Course:

MATEMATIČKE METODE U RAČUNARSTVU/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12828	Obavezan	1	5	3+1+0

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
5 credits x 40/30=6 hours and 40 minuts 3 sat(a) theoretical classes 0 sat(a) practical classes 1 excercises 2 hour(s) i 40 minuts of independent work, including consultations	Classes and final exam: 6 hour(s) i 40 minuts x 16 =106 hour(s) i 40 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 6 hour(s) i 40 minuts x 2 =13 hour(s) i 20 minuts Total workload for the subject: 5 x 30=150 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 30 hour(s) i 0 minuts Workload structure: 106 hour(s) i 40 minuts (cources), 13 hour(s) i 20 minuts (preparation), 30 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / DIGITALNA ELEKTRONIKA

Course:

DIGITALNA ELEKTRONIKA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12829	Obavezan	1	5	3+1+0

Programs
Prerequisites	The student should pass the exam in the subject Basics of Electronics.
Aims	Students learn basic digital circuits in various fabrication technologies. Through this course, students become familiar with the applications of circuits in practical applications, as well as the advantages and disadvantages of using specific circuits depending on the manufacturing technology. Also, through this course, students learn a programming language for describing and analyzing the operation of digital circuits.
Learning outcomes	After completing the course in Digital Electronics, the student who passes the course will be able to: - Analyze basic logic circuits in TTL and ECL technologies (NOR, NOR, AND, OR logic circuits); - Analyze circuits in CMOS and BiCMOS technology; - Propose solutions of logical functions in the mentioned technologies; - Interpret advantages and limitations of logic circuits in the mentioned technologies; - Analyze the working principle and illustrate the voltages in the characteristic points of astable and monostable multivibrators; - Design and implement combinational logic circuits using programmable logic circuits; - Describe and check the functionality of digital circuits in ABEL and VHDL programming languages; - Distinguish the basic types of A/D and D/A converters and define the basic principle of operation of individual converters.
Lecturer / Teaching assistant	Dr Andjela Draganic - Teacher
Methodology	Lectures, exercises, seminar papers, consultations.

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures	Coding (Hanning code, Gray code, NRZ, Manchester code,...)
I week exercises	Coding (Hanning code, Gray code, NRZ, Manchester code,...)
II week lectures	Logic circuits in TTL technology.
II week exercises	Logic circuits in TTL technology.
III week lectures	Logic circuits in ECL technology.
III week exercises	Logic circuits in ECL technology.
IV week lectures	Logic circuits in CMOS and BiCMOS technology. Realization of logic functions in CMOS technology
IV week exercises	Logic circuits in CMOS and BiCMOS technology. Realization of logic functions in CMOS technology
V week lectures	Bistable multivibrators. Astable and monostable multivibrators in CMOS technology.
V week exercises	Bistable multivibrators. Astable and monostable multivibrators in CMOS technology.
VI week lectures	Astable and monostable multivibrators implemented using the TIMER 555 circuit.
VI week exercises	Astable and monostable multivibrators implemented using the TIMER 555 circuit.
VII week lectures	Colloquium I
VII week exercises	Colloquium I
VIII week lectures	Segment indicators (Multi-digit seven-segment, LCD)
VIII week exercises	Segment indicators (Multi-digit seven-segment, LCD)
IX week lectures	Programmable logic circuits PLA and PAL
IX week exercises	Programmable logic circuits PLA and PAL
X week lectures	Programming of programmable PAL circuits. Programming languages VHDL and ABEL
X week exercises	Programming of programmable PAL circuits. Programming languages VHDL and ABEL
XI week lectures	Programming languages VHDL and ABEL
XI week exercises	Programming languages VHDL and ABEL
XII week lectures	Programming languages VHDL and ABEL
XII week exercises	Programming languages VHDL and ABEL
XIII week lectures	D/A conversion
XIII week exercises	D/A conversion
XIV week lectures	A/D conversion
XIV week exercises	A/D conversion
XV week lectures	Final test
XV week exercises	Final test

Student workload	Weekly: 5 credits x 40/30 = 6 hours and 40 minutes Structure: 3 hours of lectures 1 hour of calculus exercises 2 hours and 40 minutes of independent work, including consultations During the semester: Classes and final exam: (6 hours 40 minutes) x 16 = 106 hours 40 minutes Necessary preparations before the beginning of the semester (administration, registration, verification) 2 x (6 hours and 40 minutes) = 13 hours and 20 minutes Total workload for the course 5.0x30 = 150 hours Supplementary work for exam preparation in the make-up exam period, including taking the make-up exam from 0 to 30 hours (remaining time from the first two items to the total workload for the subject 150 hours) Load structure: 106 hours and 40 minutes. (Teaching) + 13 hours and 20 minutes. (Preparation)+30 hours (Supplementary work)
Per week	Per semester
5 credits x 40/30=6 hours and 40 minuts 3 sat(a) theoretical classes 0 sat(a) practical classes 1 excercises 2 hour(s) i 40 minuts of independent work, including consultations	Classes and final exam: 6 hour(s) i 40 minuts x 16 =106 hour(s) i 40 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 6 hour(s) i 40 minuts x 2 =13 hour(s) i 20 minuts Total workload for the subject: 5 x 30=150 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 30 hour(s) i 0 minuts Workload structure: 106 hour(s) i 40 minuts (cources), 13 hour(s) i 20 minuts (preparation), 30 hour(s) i 0 minuts (additional work)
Student obligations	Students are required to attend classes and exercises, do all homework and do both colloquiums
Consultations	After the lectures and if necessary, in agreement with the teacher.
Literature	D. Živković, M. Popović: Impulse and digital electronics, Nauka, Belgrade N. Tadić, S. Stanković. N. Lekić, M. Laković: Collection of solved problems in electronics, ETF Podgorica.
Examination methods	- 1 colloquium carries 50 points, - final exam 50 points. It is necessary to accumulate 50 points in order to pass the exam.
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / VHDL PROGRAMIRANJE

Course:

VHDL PROGRAMIRANJE/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12831	Obavezan	1	5	2+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
5 credits x 40/30=6 hours and 40 minuts 2 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 2 hour(s) i 40 minuts of independent work, including consultations	Classes and final exam: 6 hour(s) i 40 minuts x 16 =106 hour(s) i 40 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 6 hour(s) i 40 minuts x 2 =13 hour(s) i 20 minuts Total workload for the subject: 5 x 30=150 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 30 hour(s) i 0 minuts Workload structure: 106 hour(s) i 40 minuts (cources), 13 hour(s) i 20 minuts (preparation), 30 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / JAVA PROGRAMIRANJE

Course:

JAVA PROGRAMIRANJE/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12832	Obavezan	1	5	3+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
5 credits x 40/30=6 hours and 40 minuts 3 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 1 hour(s) i 40 minuts of independent work, including consultations	Classes and final exam: 6 hour(s) i 40 minuts x 16 =106 hour(s) i 40 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 6 hour(s) i 40 minuts x 2 =13 hour(s) i 20 minuts Total workload for the subject: 5 x 30=150 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 30 hour(s) i 0 minuts Workload structure: 106 hour(s) i 40 minuts (cources), 13 hour(s) i 20 minuts (preparation), 30 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / SOFTVER OTVORENOG KODA

Course:

SOFTVER OTVORENOG KODA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12833	Obavezan	1	5	2+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
5 credits x 40/30=6 hours and 40 minuts 2 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 2 hour(s) i 40 minuts of independent work, including consultations	Classes and final exam: 6 hour(s) i 40 minuts x 16 =106 hour(s) i 40 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 6 hour(s) i 40 minuts x 2 =13 hour(s) i 20 minuts Total workload for the subject: 5 x 30=150 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 30 hour(s) i 0 minuts Workload structure: 106 hour(s) i 40 minuts (cources), 13 hour(s) i 20 minuts (preparation), 30 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / NAUČNI SOFTVERSKI ALATI

Course:

NAUČNI SOFTVERSKI ALATI/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12834	Obavezan	2	6	2+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 2 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / RAČUNARSKA OBRADA SIGNALA

Course:

RAČUNARSKA OBRADA SIGNALA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12835	Obavezan	2	6	3+1+0

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 0 sat(a) practical classes 1 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / DIGITALNI VLSI DIZAJN

Course:

DIGITALNI VLSI DIZAJN/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12836	Obavezan	2	6	3+0+1

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 1 sat(a) practical classes 0 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / ALATI ZA RAZVOJ SOFTVERA

Course:

ALATI ZA RAZVOJ SOFTVERA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
12837	Obavezan	2	6	2+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 2 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / PRINCIPI MOBILNIH RADIOKOMUNIKACIJA

Course:

PRINCIPI MOBILNIH RADIOKOMUNIKACIJA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13266	Obavezan	3	6	3+1+0

Programs
Prerequisites	auto_awesome Translate from: Bosnian ​ 568 / 5,000 Translation results Translation result There are no requirements for registering, tracking and passing the course.
Aims	Students get to know the basic elements of mobile communication systems. The specifics of the mobile radio channel, principles of multiple access characteristic of mobile radio systems, techniques for improving the quality of the established mobile radio connection are studied. Students are introduced to the basic architectures of cellular mobile radio systems.
Learning outcomes	After the student passes this exam, he/she will be able to: Gain a general insight into the concept of mobile radio communication systems. Explain propagation mechanisms and signal attenuation. It defines the specifics of the mobile radio channel. Explain the techniques for improving the quality of the established mobile radio connection. Understands multiple access and duplex techniques. Explain the architecture, key technologies and services provided by mobile radio communication systems.
Lecturer / Teaching assistant	Prof. dr Zoran Veljović
Methodology	Lectures, calculation exercises and consultations.

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures	Introduction. The importance and specifics of mobile radio communications.
I week exercises	Analysis of the specifics of mobile radio communications.
II week lectures	Mechanisms of signal propagation in a mobile radio channel. Signal attenuation in free space.
II week exercises	Analysis of relations that describe attenuation in free space.
III week lectures	Multipath fading. Lognormal fading. Doppler shift, delay spread.
III week exercises	Analysis of the specifics of the mobile radio channel.
IV week lectures	Frequency and time parameters of frequency and time selectivity of multipath fading.
IV week exercises	The practical significance of time and frequency dispersivity parameters of a mobile radio channel.
V week lectures	Microscopic and macroscopic diversity. Ways of realizing diversity.
V week exercises	Analysis of the application of macroscopic and microscopic diversity.
VI week lectures	Types and ways of realization of duplex. FDMA. TDMA.
VI week exercises	Analysis of FDMA and TDMA duplex.
VII week lectures	Colloquium.
VII week exercises	Colloquium.
VIII week lectures	CDMA.
VIII week exercises	Analysis of CDMA Multiple Access.
IX week lectures	Transmission through multiple submitters. OFDM.
IX week exercises	Analysis of the OFDM technique.
X week lectures	Concept of cellular systems. Architecture and key technologies of the second generation system.
X week exercises	Analysis of the cellular concept.
XI week lectures	Elements of architecture and key technologies of third generation mobile radio communication systems.
XI week exercises	Analysis of GSM architecture.
XII week lectures	Elements of the LTE, LTE-A and LTE-Pro architectures.
XII week exercises	Analysis of UMTS architecture.
XIII week lectures	Features of 5G service.
XIII week exercises	LTE architecture analysis.
XIV week lectures	Basic elements of 5G architecture.
XIV week exercises	Concept analysis of 5G architecture.
XV week lectures	Getting to know mobile radio systems from telecommunications operators.
XV week exercises	Getting to know mobile radio systems from telecommunications operators.

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 0 sat(a) practical classes 1 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations	The student is obliged to attend all forms of teaching.
Consultations	Consultations are carried out in agreement with students.
Literature	[1] A. Nešković, Radiocommunications, Academic Thought, Belgrade, 2015. [2] S. Faruque, Radio Frequency Multiple Access Techniques Made Easy, Springer, 2019. [3] Subject teacher materials that are updated annually.
Examination methods	The colloquium carries 50 points, and the final exam 50 points.
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / PARALELNO PROGRAMIRANJE

Course:

PARALELNO PROGRAMIRANJE/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13267	Obavezan	3	6	3+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 3 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / EKSPERTNI SISTEMI

Course:

EKSPERTNI SISTEMI/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13269	Obavezan	3	6	3+1+1

Programs
Prerequisites	Software Engineering
Aims	Through this course, students become familiar with modern intelligent systems for automatic decision-making, their implementation, and application for solving specific problems, as well as in synthesis, diagnosis, and process control. The examination is through midterms and one major or several smaller projects.
Learning outcomes	After passing this exam, the student will be able to: Explain the concept, characteristics, and architecture of expert systems, as well as the concept of knowledge engineering. Identify problems that can be solved through searching. Define search problems, understand the division into uninformed and informed search algorithms, and apply them in solving relevant problems. Recognize problems suitable for solving with basic data science techniques. Apply basic data science techniques. Create expert systems using the Experta library in Python.
Lecturer / Teaching assistant	Professor: Prof. Vesna Popović-Bugarin, PhD Associate: Danilo Planinić
Methodology	Lectures, exercises, consultations, and independent work on solving practical problems.

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures	General information on natural and artificial intelligence. The history of artificial intelligence.
I week exercises	Examples of expert systems programmed in Experta. Examples of well-known expert systems (Eliza...).
II week lectures	Expert systems (ES) architecture, concept of ES, knowledge engineering. Knowledge representation.
II week exercises	Tasks that illustrate the concepts of knowledge representation.
III week lectures	Search, defining search problems, uninformed search strategies.
III week exercises	Tasks that illustrate concepts of knowledge representation, defining problems that can be solved through searching, and basic search strategies.
IV week lectures	Informed search strategies.
IV week exercises	Tasks that illustrate the use of informed search strategies.
V week lectures	Selection of heuristic functions. Hill climbing.
V week exercises	Tasks involving the use of informed search strategies. Defining and selecting heuristics.
VI week lectures	Midterm exam
VI week exercises	Midterm exam
VII week lectures	Data Science. K-nearest neighbors.
VII week exercises	Implementation of problems solved by the K-nearest neighbors method in Python.
VIII week lectures	Naive Bayesian networks.
VIII week exercises	Implementation of problems solved using the Naive Bayesian networks method in Python.
IX week lectures	Recommendation systems.
IX week exercises	Implementation of recommendation systems in Python.
X week lectures	Decision trees.
X week exercises	Implementation of problems solved by the decision tree method in Python.
XI week lectures	Second midterm exam
XI week exercises	Second midterm exam
XII week lectures	Experta – Introduction (facts, rules)
XII week exercises	Experta – Introduction (facts, rules)
XIII week lectures	Experta – pattern matching, field value constraints
XIII week exercises	Implementation of planning problems in Experta
XIV week lectures	Experta – complex pattern matching
XIV week exercises	Implementation of a simple game in Experta
XV week lectures	Make-up midterm exam
XV week exercises	Make-up midterm exam

Student workload	Weekly: 6 credits x 40/30 = 8 hours Structure: 3 hours of lectures 1 hour of computer exercises 1 hour of laboratory exercises 3 hours of independent work, including consultations
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 1 sat(a) practical classes 1 excercises 3 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations	Students are required to attend classes and solve practical problems, the solutions to which they present publicly.
Consultations	As needed and in agreement with students.
Literature	Primary– Material from lectures and exercises (script), Dragan Bojić, Miloš Gligorić, Boško Nikolić: Collection of Problems from Expert Systems, Belgrade, 2009 Additional – S.J.Russell, P.Norvig: Artificial Intelligence, A Modern Approach, Prentice Hall, 2nd ed., 2002. Joseph C. Giarratano, Gary D. Riley: Expert Systems: Principles and Programming, Prentice Hall, 2nd ed., 2002. (for mastering the material and preparing seminar papers)
Examination methods	Forms of knowledge assessment and grading: - Homework and participation in lectures: 25 points; - First midterm exam: 35 points; - Second midterm exam: 25 points; - Implementation of an expert system and work assessment is graded up to a maximum of 15 points.
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / SAVREMENE ICT TEHNOLOGIJE

Course:

SAVREMENE ICT TEHNOLOGIJE/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13270	Obavezan	3	6	3+0+2

Programs
Prerequisites	None
Aims	Students become acquainted with the fundamentals of CPS (Cyber-Physical Systems) and acquire the knowledge needed for planning, designing, and implementing CPS services using modern communication and computing technologies.
Learning outcomes	After passing this exam, students will be able to: Design CPS (Cyber-Physical Systems) in accordance with the communication and computing requirements of the application. Understand the role of different application layer protocols in IoT networks. Comprehend the concept of microservices and apply tools for microservice orchestration. Utilize the HDFS (Hadoop Distributed File System). Develop scalable applications for distributed data processing. Apply tools for real-time data processing
Lecturer / Teaching assistant	Doc. dr Slavica Tomovic
Methodology	Lectures, labs, consultations

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures	Introduction to the course concept. Introduction to Cyber-Physical Systems (CPS).
I week exercises	Introduction to Cyber-Physical Systems (CPS).
II week lectures	The architecture of the Internet of Things (IoT). Application domains and implementation challenges.
II week exercises	The architecture of the Internet of Things (IoT). Application domains and implementation challenges.
III week lectures	Convergence of IoT protocols (MQTT, CoAP, AMQP, JMS, DDS, REST, XMPP).
III week exercises	MQTT and CoAP
IV week lectures	Sensor networks: architecture and wireless technologies (ZigBee, 6LoWPAN, LORA, Bluetooth).
IV week exercises	Sensor networks: architecture and wireless technologies (ZigBee, 6LoWPAN, LORA, Bluetooth).
V week lectures	Processing of sensor data using cloud services.
V week exercises	Processing of sensor data using cloud services.
VI week lectures	IoT operating systems and open-source platforms.
VI week exercises	IoT operating systems and open-source platforms.
VII week lectures	Midterm exam.
VII week exercises	Midterm exam.
VIII week lectures	Cloud technology. Web services and Service-Oriented Architecture (SOA).
VIII week exercises	Cloud technology. Web services and Service-Oriented Architecture (SOA).
IX week lectures	Objectives and concepts of virtualization. Virtualization technologies.
IX week exercises	Objectives and concepts of virtualization. Virtualization technologies.
X week lectures	Microservice orchestration.
X week exercises	Microservice orchestration.
XI week lectures	Networking in data centers. Software-defined networks.
XI week exercises	Networking in data centers. Software-defined networks.
XII week lectures	High-performance processing in the cloud (Hadoop, HDFS).
XII week exercises	High-performance processing in the cloud (Hadoop, HDFS).
XIII week lectures	MapReduce.
XIII week exercises	MapReduce.
XIV week lectures	Apache Spark.
XIV week exercises	Apache Spark.
XV week lectures	Real-time data processing. Apache Kafka.
XV week exercises	Real-time data processing. Apache Kafka.

Student workload	6 credits x 40/30 = 8 hours per week
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 3 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations	Students are required to attend classes, take the midterm exam, and the final exam.
Consultations	One hour once per week.
Literature	1. Ian Foster, Dennis B. Gannon, “Cloud computing for science and engineering”, The MIT Press, 2017. 2. D. Hanes, G. Salgueiro, P. Grossetete, R. Barton, and J. Henry, “IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things”, Cisco Press, 2017. 3. Larry Peterson, Carmelo Cascone, Brian OConnor, Thomas Vachuska, and Bruce Davie, “Software-Defined Networks: A Systems Approach”, 2021.
Examination methods	Midterm exam, final exam, lab tests
Special remarks
Comment	Lectures and laboratory exercises (L+Lab) are conducted for groups of up to 40 students.

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / IZBORNI PREDMET 2- IOT MREŽE

Course:

IZBORNI PREDMET 2- IOT MREŽE/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13271	Obavezan	3	6	3+0+1

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 1 sat(a) practical classes 0 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / M2M KOMUNIKACIONI SISTEMI

Course:

M2M KOMUNIKACIONI SISTEMI/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13280	Obavezan	3	6	1+0+2

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 1 sat(a) theoretical classes 2 sat(a) practical classes 0 excercises 5 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / TEORIJA ALGORITAMA

Course:

TEORIJA ALGORITAMA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13294	Obavezan	3		2+2+0

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
credits x 40/30=0 hours and 0 minuts 2 sat(a) theoretical classes 0 sat(a) practical classes 2 excercises -4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 0 hour(s) i 0 minuts x 16 =0 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 0 hour(s) i 0 minuts x 2 =0 hour(s) i 0 minuts Total workload for the subject: x 30=0 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 0 hour(s) i 0 minuts Workload structure: 0 hour(s) i 0 minuts (cources), 0 hour(s) i 0 minuts (preparation), 0 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / KOMPJUTERSKA VIZIJA

Course:

KOMPJUTERSKA VIZIJA/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13296	Obavezan	3	6	2+1+0

Programs
Prerequisites	Fundamentals of Machine Learning and Artificial Intelligence
Aims	Through this course, students become familiar with modern computer vision methods based on deep learning, popular programming libraries for working with neural networks. Additionally, students are introduced to the three basic tasks of computer vision - image classification, image segmentation, and object detection in images.
Learning outcomes	After passing this exam, the student will be able to correctly use the Keras and TensorFlow programming libraries, create a model of a fully connected neural network according to the given specification, create a model of a convolutional neural network according to the given specification, perform image classification through deep learning in a predefined image database, and perform image segmentation through deep learning.
Lecturer / Teaching assistant	Prof. dr Nikola Žarić BSc Danilo Planinić
Methodology	Lectures and exercises in a computer classroom / laboratory. Learning and independent completion of practical tasks. Consultations.

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures	Introduction to computer vision. Review of linear algebra material.
I week exercises	Review of linear algebra material.
II week lectures	Python – review. Working with the Keras and TensorFlow libraries.
II week exercises	Python, Numpy, TensorFlow, Keras
III week lectures	Mathematical model of neural networks. Representation of data for neural networks. Working with tensors.
III week exercises	Mathematical model of neural networks. Representation of data for neural networks. Working with tensors.
IV week lectures	Gradient optimization method. Backpropagation.
IV week exercises	Training the first neural network
V week lectures	Deep learning. Convolutional neural networks. Building blocks of convolutional neural networks.
V week exercises	Training the first convolutional neural network
VI week lectures	Convolutional neural networks – well-known architectures.
VI week exercises	--
VII week lectures	Midterm exam
VII week exercises	Midterm exam
VIII week lectures	Image classification.
VIII week exercises	Training a convolutional neural network for image classification
IX week lectures	Image classification – continuation.
IX week exercises	Image classification.
X week lectures	Image segmentation.
X week exercises	Image segmentation.
XI week lectures	Object detection in images. Popular models.
XI week exercises	Object detection in images. Popular models.
XII week lectures	Techniques for enhancing deep network training (data augmentation). Using pre-trained models - fine-tuning the network.
XII week exercises	Techniques for enhancing deep network training (data augmentation). Using pre-trained models - fine-tuning the network.
XIII week lectures	Make-up exam for the midterm
XIII week exercises	Make-up exam for the midterm
XIV week lectures	Presentations of student projects
XIV week exercises	Presentations of student projects
XV week lectures	Presentations of student projects
XV week exercises	Presentations of student projects

Student workload	6 credits x 40/30 = 8 hours
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 2 sat(a) theoretical classes 0 sat(a) practical classes 1 excercises 5 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations	Regular attendance at lectures, appropriate behavior, participation in assessments (midterms and final project).
Consultations	By agreement
Literature	François Chollet, Deep Learning with Python, Second Edition, Manning Publications Co, 2021.
Examination methods	Midterm exam: total of 50 points Project: total of 50 points Note: To be eligible to work on the project, the student must score at least 50% on the midterm exam.
Special remarks
Comment	To be eligible to work on the project, the student must score at least 50% on the midterm exam.

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points

Faculty of Electrical Engineering / / TEHNIKA DIZAJNIRANJA ARH. SPECIJALIZOVANE NAMJENE

Course:

TEHNIKA DIZAJNIRANJA ARH. SPECIJALIZOVANE NAMJENE/

Course ID	Course status	Semester	ECTS credits	Lessons (Lessons+Exercises+Laboratory)
13297	Obavezan	3	6	3+0+1

Programs
Prerequisites
Aims
Learning outcomes
Lecturer / Teaching assistant
Methodology

Plan and program of work
Preparing week	Preparation and registration of the semester
I week lectures
I week exercises
II week lectures
II week exercises
III week lectures
III week exercises
IV week lectures
IV week exercises
V week lectures
V week exercises
VI week lectures
VI week exercises
VII week lectures
VII week exercises
VIII week lectures
VIII week exercises
IX week lectures
IX week exercises
X week lectures
X week exercises
XI week lectures
XI week exercises
XII week lectures
XII week exercises
XIII week lectures
XIII week exercises
XIV week lectures
XIV week exercises
XV week lectures
XV week exercises

Student workload
Per week	Per semester
6 credits x 40/30=8 hours and 0 minuts 3 sat(a) theoretical classes 1 sat(a) practical classes 0 excercises 4 hour(s) i 0 minuts of independent work, including consultations	Classes and final exam: 8 hour(s) i 0 minuts x 16 =128 hour(s) i 0 minuts Necessary preparation before the beginning of the semester (administration, registration, certification): 8 hour(s) i 0 minuts x 2 =16 hour(s) i 0 minuts Total workload for the subject: 6 x 30=180 hour(s) Additional work for exam preparation in the preparing exam period, including taking the remedial exam from 0 to 30 hours (remaining time from the first two items to the total load for the item) 36 hour(s) i 0 minuts Workload structure: 128 hour(s) i 0 minuts (cources), 16 hour(s) i 0 minuts (preparation), 36 hour(s) i 0 minuts (additional work)
Student obligations
Consultations
Literature
Examination methods
Special remarks
Comment

Grade:	F	E	D	C	B	A
Number of points	less than 50 points	greater than or equal to 50 points and less than 60 points	greater than or equal to 60 points and less than 70 points	greater than or equal to 70 points and less than 80 points	greater than or equal to 80 points and less than 90 points	greater than or equal to 90 points