Skip to main content

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