Data AnalyticsLaajuus (5 cr)
Code: AL00CJ78
Credits
5 op
Teaching language
- Finnish
Objective
The student can:
- describe the steps of the data analytics process and understand the role of data analytics in modern business
- combine information sources of different content and different forms into usable data matrices
- use tools in gathering, describing, and visualizing various types of information
- produce and interpret key statistical measures and figures
- construct a simple predictive model using machine learning methods and evaluate its quality
Enrollment
20.11.2024 - 03.01.2025
Timing
07.01.2025 - 30.04.2025
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Business and Hospitality Management (LAB)
Campus
E-campus
Teaching languages
- Finnish
Seats
20 - 50
Degree programmes
- Complementary competence, Bachelor's (in Finnish)
Teachers
- Antti Salopuro
Scheduling groups
- Luennot 1 (Size: 0. Open UAS: 0.)
- Avoimen ammattikorkeakoulun kiintiö (Size: 10. Open UAS: 10.)
Groups
-
LLABTOIT
-
LLABTO24-25
-
LLPRLII22SL
Small groups
- Lecture 1
- Open UAS quota
Learning outcomes
The student can:
- describe the steps of the data analytics process and understand the role of data analytics in modern business
- combine information sources of different content and different forms into usable data matrices
- use tools in gathering, describing, and visualizing various types of information
- produce and interpret key statistical measures and figures
- construct a simple predictive model using machine learning methods and evaluate its quality
Implementation and methods of teaching
Lectures, weekly lab exercises, miniproject. Lectures in class, streamed.
Assessment scale
1-5
Enrollment
20.11.2023 - 05.01.2024
Timing
08.01.2024 - 25.04.2024
Number of ECTS credits allocated
5 op
Virtual portion
5 op
Mode of delivery
Distance learning
Unit
Faculty of Business and Hospitality Management (LAB)
Campus
E-campus
Teaching languages
- Finnish
Degree programmes
- Complementary competence, Bachelor's (in Finnish)
Teachers
- Antti Salopuro
Scheduling groups
- Luennot (Size: 0. Open UAS: 0.)
Groups
-
LLABTO23-24
Small groups
- Lecture
Learning outcomes
The student can:
- describe the steps of the data analytics process and understand the role of data analytics in modern business
- combine information sources of different content and different forms into usable data matrices
- use tools in gathering, describing, and visualizing various types of information
- produce and interpret key statistical measures and figures
- construct a simple predictive model using machine learning methods and evaluate its quality
Implementation and methods of teaching
Lectures, weekly lab exercises, miniproject
Assessment scale
1-5