AI and data structuring in quality control Field of study: Quality Control Materials and Products
Programme code: W4-S2KJ25.2025

Module name: AI and data structuring in quality control
Module code: KJ2A_AISDKJ
Programme code: W4-S2KJ25.2025
Semester: summer semester 2026/2027
Language of instruction: Polish
Form of verification: exam
ECTS credits: 4
Purpose and description of the content of education:
Students gain knowledge in the use of artificial intelligence (AI) and data structuring methods in quality control processes. The module focuses on the application of selected data analysis tools and techniques that support the identification of nonconformities, production error prediction, risk assessment, and data-driven decision-making. The course covers the fundamentals of machine learning and its applications in qualitative data analysis. Particular attention is paid to the data structuring process – from collecting information from various sources, through data cleaning, normalization, and integration, to visualization and analysis. Students learn tools such as Excel Power Query, Python (pandas and scikit-learn libraries), Jupyter Notebook, as well as the basics of working with databases and dashboards (e.g., Power BI, Tableau).
List of modules that must be completed before starting this module (if necessary): not applicable
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
Rozumie podstawowe pojęcia związane z AI, uczeniem maszynowym i eksploracją danych w kontekście kontroli jakości. [KJ2A_AISDKJ_1]
 KJ2A_W09 [3/5] KJ2A_K01 [3/5]
Potrafi pozyskać, przekształcić i zintegrować dane pochodzące z różnych etapów procesu produkcyjnego oraz systemów monitorujących jakość. [KJ2A_AISDKJ_2]
 KJ2A_U01 [3/5] KJ2A_U02 [3/5] KJ2A_U08 [3/5]
Posiada umiejętność wizualizacji danych i prezentacji wyników analiz w sposób wspomagający podejmowanie decyzji. [KJ2A_AISDKJ_3]
 KJ2A_U01 [3/5] KJ2A_U07 [3/5] KJ2A_U08 [3/5]
Wykazuje świadomość ograniczeń i ryzyk związanych z automatyzacją decyzji w procesach jakościowych. [KJ2A_AISDKJ_4]
 KJ2A_K01 [3/5]
Form of teaching Number of hours Methods of conducting classes Assessment of the learning outcomes Learning outcomes
lecture [KJ2A_AISDKJ_fs_1] 15 Formal lecture/ course-related lecture [a01] 
Problem-based lecture [b01] 
Screen presentation [c07]  		exam KJ2A_AISDKJ_1 KJ2A_AISDKJ_2 KJ2A_AISDKJ_3 KJ2A_AISDKJ_4
laboratory classes [KJ2A_AISDKJ_fs_2] 30 Explanation/clarification [a05] 
Working with a computer [d01] 
Working with a programmed textbook [d02] 
Self-education [f01] 
Individual work with a text [f02] 
Conceptual work [f03]  		course work KJ2A_AISDKJ_1 KJ2A_AISDKJ_2 KJ2A_AISDKJ_3 KJ2A_AISDKJ_4
The student's work, apart from participation in classes, includes in particular:
Name Category Description
Search for materials and review activities necessary for class participation [a01] Preparation for classes
reviewing literature, documentation, tools and materials as well as the specifics of the syllabus and the range of activities indicated in it as required for full participation in classes
Literature reading / analysis of source materials [a02] Preparation for classes
reading the literature indicated in the syllabus; reviewing, organizing, analyzing and selecting source materials to be used in class
Developing practical skills [a03] Preparation for classes
activities involving the repetition, refinement and consolidation of practical skills, including those developed during previous classes or new skills necessary for the implementation of subsequent elements of the curriculum (as preparation for class participation)
Determining the stages of task implementation contributing to the verification of learning outcomes [c01] Preparation for verification of learning outcomes
devising a task implementation strategy embracing the division of content, the range of activities, implementation time and/or the method(s) of obtaining the necessary materials and tools, etc.
Implementation of an individual or group assignment necessary for course/phase/examination completion [c03] Preparation for verification of learning outcomes
a set of activities aimed at performing an assigned task, to be executed out of class, as an obligatory phase/element of the verification of the learning outcomes assigned to the course
Analysis of the corrective feedback provided by the academic teacher on the results of the verification of learning outcomes [d01] Consulting the results of the verification of learning outcomes
reading through the academic teacher’s comments, assessments and opinions on the implementation of the task aimed at checking the level of the achieved learning outcomes
Development of a corrective action plan as well as supplementary/corrective tasks [d02] Consulting the results of the verification of learning outcomes
reviewing and selecting tasks and activities enabling the elimination of errors indicated by the academic teacher, their verification or correction resulting in completing the task with at least the minimum passing grade
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)