Data-analytiikka 1 (5 cr)
Code: YC00CT52-3001
General information
- Enrollment
-
01.08.2025 - 11.01.2026
Registration for introductions has not started yet.
- Timing
-
12.01.2026 - 31.05.2026
The implementation has not yet started.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 0 cr
- Virtual portion
- 5 cr
- RDI portion
- 2 cr
- Mode of delivery
- Distance learning
- Unit
- Teknologia
- Teaching languages
- Finnish
- Degree programmes
- Data-analytiikka ja liiketoiminnan kehittäminen
- Teachers
- Master Opex Virtuaali Master Opex Virtuaali
- Groups
-
DAY25SDAY25S
-
TTY25STTY25S
- Course
- YC00CT52
Objective
The aim of the course is to give students a basic understanding of data collection, pre-processing, the use of different data storage solutions, basic statistical analysis and its importance in decision making. The course also includes practical exercises with common analytical tools (Excel, R, Python), which allow students to apply what they have learned in practice.
- The student understands the principles of data collection and pre-processing and can explain their importance in the analytical process.
- Identify different data storage solutions and assess their suitability for different needs.
- The student will be able to apply basic statistical analysis methods and use analytical tools to perform basic analyses.
- Students will be able to analyse the results of statistical analysis and assess their implications for decision making.
- The student will be able to apply the skills learned in practical exercises and be able to use analytical tools to support decision making.
Content
Centria toteuttaa
Evaluation scale
0 - 5
Further information
Kurssin toteuttaa Centria. Kts. https://centria.opinto-opas.fi/curricula
Objective
The aim of the course is to give students a basic understanding of data collection, pre-processing, the use of different data storage solutions, basic statistical analysis and its importance in decision making. The course also includes practical exercises with common analytical tools (Excel, R, Python), which allow students to apply what they have learned in practice.
- The student understands the principles of data collection and pre-processing and can explain their importance in the analytical process.
- Identify different data storage solutions and assess their suitability for different needs.
- The student will be able to apply basic statistical analysis methods and use analytical tools to perform basic analyses.
- Students will be able to analyse the results of statistical analysis and assess their implications for decision making.
- The student will be able to apply the skills learned in practical exercises and be able to use analytical tools to support decision making.
Content
Centria toteuttaa