Introduction to Data Economy (1 cr)
Code: HY00BT31-3003
General information
- Enrollment
-
29.11.2021 - 23.05.2022
Registration for the implementation has ended.
- Timing
-
01.12.2021 - 30.06.2022
Implementation has ended.
- Number of ECTS credits allocated
- 1 cr
- Local portion
- 0 cr
- Virtual proportion
- 1 cr
- Mode of delivery
- Distance learning
- Campus
- Laurea Virtual Campus
- Teaching languages
- English
- Seats
- 0 - 300
- Degree programmes
- Complementary competence, master’s studies in English (CYJ2), Generic studies
- Teachers
- Anssi Mattila
- Suvi Valsta
- Teacher in charge
- Anssi Mattila
- Scheduling groups
- Pienryhmä 1 (Size: 100 . Open UAS : 100.)
- Small groups
- Pienryhmä 1
- Study unit
- HY00BT31
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
Materials
All necessary materials are provided on the course platform.
Teaching methods
Online course available for independent study at the student's own pace
Employer connections
Course has been produced in corporation with Osaango Oy. Lecturers on the videos are experts in data economy.
Exam schedules
-
International connections
Kurssia tarjotaan yhteistyöoppilaitoksille ja sen sisältö on rakennettu sopimaan sekä EU-maihin että kansainvälisesti soveltuvaksi.
Completion alternatives
-
Student workload
1 ECTS credits = 27 hours of work
Content 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
Evaluation scale
Approved/Failed
Further information
Inquiries for the course can be directed to mooc@laurea.fi.