Course Syllabus

Bialystok University of Technology Faculty of Computer Science
Field of study Data Science Degree level and
programme type
Engineer's degree
full-time programme
Specialization/
diploma path
Study profile academic
Course name Time Series and Forecasting Course code DS1S4SCP
Course type obligatory
Forms and number of hours of tuition L C LC P SW FW S Semester 4
30 30 No. of ECTS credits 4
Program valid from 2025/2026
Entry requirements Linear Algebra 1 (DS1S1AL1),   Linear Algebra 1 (DS1S2AL2),   Algorithms and Data Structures (DS1S4ASD),   Calculus 1 (DS1S1AM1),   Calculus 2 (DS1S2AM2),   Mathematical Statistics (DS1S3SMA),  
Course objectives
Framework content
Other information about the course the course is related to the scientific research conducted at the University
Calculation: Student workload (in hours): Total
hours
Including
contact hours
Including
practical hours
30 30
30 30 30
4 4
12
12 12
12 12
Cumulative hours: 100 64 54
Cumulative number of ECTS credits: 4 2.6 2.2
Expected program-specific learning outcomes Knowledge Skills Social
competences
DS1_W01 DS1_U03
DS1_W08 DS1_U09
DS1_U17
DS1_U19
Objectives and framework content formulated by dr Dariusz Kacprzak Date: 29/05/2025
Implemented in the academic year 2026/2027
 
Course objectives
1.
. -
Teaching methods
(stationary)
-
-
Teaching methods
(remote)
-
-
Assessment methods
-
-
Assessment conditions
-
-
Symbol of
learning outcome
Intended learning outcomes Type of tuition during which the outcome is assessed
Knowledge Skills Social
competences
Knowledge: the student knows and understands
E1
E2
Skills: the student can
E3
E4
E5
Symbol of
learning outcome
Method of learning outcome verification Form of classes where verification takes place
E1 -
E2 -
E3 -
E4 -
E5 -
Basic references
1.
. -
Supplementary references
1.
. -
Course coordinator: dr Marzena Filipowicz-Chomko, dr Dariusz Kacprzak Date: 30/05/2025