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 Mathematical Statistics E Course code DS1S3SMA
Course type obligatory
Forms and number of hours of tuition L C LC P SW FW S Semester 3
30 30 No. of ECTS credits 5
Program valid from 2025/2026
Entry requirements Linear Algebra 1 (DS1S2AL2),   Calculus 2 (DS1S2AM2),   Probability Theory (DS1S2RPR),  
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
15
46 46
Cumulative hours: 125 64 76
Cumulative number of ECTS credits: 5 2.6 3.0
Expected program-specific learning outcomes Knowledge Skills Social
competences
DS1_W01 DS1_U01 DS1_K01
DS1_W02 DS1_U03
DS1_U19
Objectives and framework content formulated by dr hab. Dorota Mozyrska 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
E3
Skills: the student can
E4
E5
E6
Social competences: the student is ready to
E7
E8
Symbol of
learning outcome
Method of learning outcome verification Form of classes where verification takes place
E1 -
E2 -
E3 -
E4 -
E5 -
E6 -
E7 -
E8 -
Basic references
1.
. -
Supplementary references
1.
. -
Course coordinator: dr hab. Dorota Mozyrska, dr hab. Małgorzata Wyrwas Date: 30/05/2025