Subject

Sharing and Calculating in a Crowd

Course Title

Sharing and Calculating in a Crowd
Crowdsourcing and human computing

Code

F23L3S162

Study Programme

—

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

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

First Cycle

Academic year / semester

8 / Summer

Number of ECTS credits

Teacher

Saso Gramatikov

Prerequisites for enrolling in the course

Artificial Intelligence or Introduction to Data Science or Machine Learning

10.

Objectives of the course programme (competences)

The goal of the course is to introduce students to the crowd's ability to share and process data, enabling the resolution of problems that remain complex for computer systems but are very simple for a collective of human intelligence. The course will introduce students to a new application design and programming concept based on the untrusted participation of a large number of individuals from the crowd. The course will examine existing applications and platforms for data collection and the on-demand execution of large-scale tasks.

11.

Course content

1. Вовед во пресметување и споедлување во топа
2. Платформи за споделување во толпа
3. Работни проблеми при споделување во толпа
4. Програмски парадигми. Дизајн на алгоритми за споделено пресметување.
5. Работни текови за споделување во толпа
6. Споделување во толпа и интелигентни системи
7. Напади и заштита при споделување во толпа
8. Преглед на апликации базирани на споделување во толпа
9. Економија на апликации базирани на споделување во толпа. Инвестиција во толпа.
10. Интелигенција на јато
11. Алгоритми за пресметување во јато
12. Системи и апликации на врмрежени мобилни јазли

12.

Learning methods

Lectures supported by slide presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lecturers, independent preparation and defense of a project assignment and seminar paper, learning in an electronic environment (forums, consultations).

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	30 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	45 hours

16.

Other forms of activities

16.1.	Project assignments	15 hours
16.2.	Independent assignments	15 hours
16.3.	Home study	75 hours

17.

Assessment method

17.1.	Tests	10 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activities and learning	10 points
17.4.	Final exam	70 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

Activities 15.1 and 15.2 completed

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. Cass R. Sunstein \| Infotopia - How many minds produce knowledge \| Oxford University Press \| 2006 2. Edith Law, Luis von Ahn \| Human Computation \| Morgan&Claypool publishers \| 2011 3. Pietro Michelucci \| Handbook of Human Computation \| Springer \| 2013
22.2.	Additional literature No. Author Title Publisher Year