Subject

Introduction to Data Science

Course Title

Introduction to Data Science
Introduction to Data Science

Code

F18L3W008

Study Programme

Application of Information Technologies, Software Engineering, and Information Systems

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

5 / Winter

Number of ECTS credits

Teacher

—

Prerequisites for enrolling in the course

Business Statistics or Probability and Statistics or Fundamentals of Information Theory

10.

Objectives of the course programme (competences)

Introduction to the fundamentals of data-driven science. Students will be introduced to the process and methodology of working with data, starting with problem identification, followed by data collection, and then processing. Students will learn the basic techniques for data processing and pattern identification, as well as methods for visualizing and interpreting the results obtained.

11.

Course content

(1) Introduction to Data Science as the Fourth Scientific Paradigm
(2) Designing experiments and identifying problems
(2) Collection and processing of data
(2) Data analysis
(2) Identification of patterns in the data
(2) Explanation of the obtained hypotheses
(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 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	0 points
17.2.	Seminar paper / project (presentation: written and oral)	15 points
17.3.	Activities and learning	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.

Requirement for obtaining a signature and taking the final exam

Activities 15.2 and 16.1 have been 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 No. Author Title Publisher Year
22.2.	Additional literature No. Author Title Publisher Year