Introduction to Data Economy (1 cr)
Code: HY00BT31-3010
General information
Enrollment
20.05.2024 - 24.11.2024
Timing
01.06.2024 - 31.12.2024
Number of ECTS credits allocated
1 op
Virtual proportion
1 op
Mode of delivery
Distance learning
Unit
Korkeakouluyksikkö D, Leppävaara, tiko
Campus
Laurea Virtual Campus
Teaching languages
- English
Seats
0 - 500
Degree programmes
- Complementary competence, master’s studies in English (CYJ2), Generic studies
Teachers
- Lea Virta
- Niklas Leppä
Teacher in charge
Anssi Mattila
Groups
-
TYJ24SJTäydentävä osaaminen (yamk-tutkinto), S24, yhteiset opinnot
-
CYJ24SJComplementary competence (master’s studies in English), S24, Generic studies
Learning outcomes
Student is able to
- Explain why organizations need to apply data in decision making
- Explain where the data comes from and how it can be used (buying, selling, collecting data, big data from IoT, digital platforms and APIs, machine learning and AI vs. statistical methods)
- Identify the role of information in a value creation process
- Identify key business models enabled by digital data
- List a few “no-code” ways of experimenting with data products to validate the business model
- Summarize how intellectual privacy regulations shape the data economy
Teaching methods
Online course available for independent study at the student's own pace
Learning materials and recommended literature
All necessary materials are provided on the course platform.
Alternative completion methods of implementation
-
Co-operation with working life and/or RDI
Course has been produced in corporation with Osaango Oy. Lecturers on the videos are experts in data economy.
Important dates
The course has to be completed in Canvas until end of the course end date (31.12.2024).
During the summer holiday in July and during the New Year holidays, no credits are registered. Credits made by the end of the semester are recorded for the past semester, those made by 31.12. for the autumn semester, and those made by 31.7. for the spring semester.
Forms of internationality
The course is offered to partner institutions and its content is designed to be suitable for both EU countries and internationally.
Students workload
1 ECTS credits = 27 hours of work
Content and scheduling
Videos, quizzes and articles in four different modules.
Module 1: Data economy in brief
Module 2: Data sources and business models
Module 3: Role of information in value creation
Module 4: Next steps in data economy
After this course, you will be able to:
Explain why organizations need to apply data in decision making
Explain where the data comes from and how it can be used (buying, selling, collecting data, big data from IoT, digital platforms and APIs, machine learning and AI vs. statistical methods)
Identify the role of information in a value creation process
Identify key business models enabled by digital data.
List a few “no-code” ways of experimenting with data products to validate the business model
Summarize how privacy regulations shape the data economy
Further information for students
The course is master's level and therefore bachelor's level degree student can not enroll for the course.
Inquiries for the course can be directed to mooc@laurea.fi.
Grading scale
Approved/Failed
Evaluation methods and criteria
For a passing grade, student has to complete all the required tests with a minimum score of 50%, all the required assignments and familiarise themselves with the course materials.