Introduction to Data Economy (1 cr)
Code: HY00BT31-3001
General information
Enrollment
01.01.2021 - 30.06.2021
Timing
01.01.2021 - 31.08.2021
Number of ECTS credits allocated
1 op
Virtual proportion
1 op
Mode of delivery
Distance learning
Unit
Korkeakouluyksikkö D /YAMK
Campus
Laurea Virtual Campus
Teaching languages
- English
Seats
0 - 50
Degree programmes
- Complementary competence, master’s studies in English (CYJ2), Generic studies
Teachers
- Katariina Husman
- Suvi Valsta
Scheduling groups
- Pienryhmä 1 (Size: 50. Open UAS: 50.)
Groups
-
CYJ21KJComplementary competence (master’s studies in English), K21, Generic studies
Small groups
- Pienryhmä 1
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
Independently studied online course.
Location and time
At your own pace starting 15.3.2021
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
-
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
Inquiries for the course can be directed to mooc@laurea.fi.
Grading scale
Approved/Failed
Evaluation criteria, approved/failed
You need to pass each quiz with a 50% grade to pass this course. Additionally, remember to mark each lesson completed in order to pass the course