Objectives and competences
Use advanced tools for data preparation, analysis and visualisation.
Content (Syllabus outline)
Developing content and tools that offer data preparation, analysis and visualisation as a basis for independent work.
Learning and teaching methods
Seminar with practical demonstration and preparation for independent work
Intended learning outcomes - knowledge and understanding
Knowledge and understanding:
- an in-depth understanding of data visualisation and analytics, statistical analysis and data engineering, specifically in the business domain
Intended learning outcomes - transferable/key skills and other attributes
Cognitive/Intellectual skills:
- Understanding and ability to use massive data and techniques from data science, artificial intelligence and machine learning, specifically in the field of business.
Key/Transferable skills
- discovering ways to create added value from the skills acquired
Practical skills:
- Ability to use RapidMiner, and other relevant software solutions.
Readings
Temeljna literatura:
• Bidgoli, H. (2021). Management information systems. Cengage Learning. ISBN - 978-0-357-41869-7
COBISS.SI-ID - 144315139
• PERKO, Igor. Managerski informacijski sistemi : zapiski predavanj in učna e-gradiva. Maribor: Ekonomsko-poslovna fakulteta, 2019. 100 str., graf. prikazi, tabele. [COBISS.SI-ID 13436700]
Dodatna literatura:
• Altair RapidMiner Academy(2023) https://academy.rapidminer.com/
Additional information on implementation and assessment - examination,
- project
