Introduction to Data Science

Course title

Code

F18L3W008

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

5 / Winter

Number of ECTS credits

Teacher

—

Prerequisites for enrolling in the course

Бизнис статистика или Веројатност и статистика или Основи на теорија на информации

10.

Course objectives (competences)

Students will obtain knowledge with the Data Science fundamentals and they will be introduced to the process and methodologies for operations with data, starting from problem identification, data collection and data processing. At the end of the course students would know the basic techniques for data processing and pattern recognition in the data, as well as, they will know how to visualize the results and properly interpret them.

11.

Course content

(1) Introduction to Data Science as a fourth science paradigm
(2) Designing experiments and problem identification
(2) Collecting data and data processing
(2) Data Analysis
(2) Pattern recognition in the data
(2) Explanation of the obtained hypothesis
(2) Hypothesis testing and feedback

12.

Learning methods

Lectures using presentations, interactive lectures, exercises (using equipment and software packages), teamwork, case studies, guest lecturers, independent preparation and defense of a project assignment and a seminar paper.

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of the available time

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

15.

Forms of teaching activities

15.1.	Lectures – theoretical teaching	30 hours
15.2.	Exercises (laboratory, auditory), seminars, team work	45 hours

16.

Other forms of activities

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

17.

Grading

17.1.	Tests	0 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activity and participation	15 points
17.4.	Final exam	65 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

Activities 15.2 and 16.1 have been completed.

20.

Language of instruction

Macedonian and English

21.

Method of monitoring teaching quality

internal evaluation and survey mechanism

22.

Literature

22.1.	Required literature No. Author Title Publisher Year
22.2.	Additional literature No. Author Title Publisher Year