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Introduction to Data Economy (1 cr)

Code: C-02629-HY00BT31-3012

General information


Enrollment
19.05.2025 - 23.11.2025
Registration for introductions has not started yet.
Timing
01.06.2025 - 31.12.2025
The implementation has not yet started.
Number of ECTS credits allocated
1 cr
Institution
Laurea University of Applied Sciences, Laurea Verkkokampus
Teaching languages
English
Seats
0 - 300
No reservations found for realization C-02629-HY00BT31-3012!

Evaluation scale

Approved/Failed

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

Objective

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

Location and time

In the Canvas online learning environment during the duration of the course. See Timing.

Materials

All necessary materials are provided on the course platform.

Teaching methods

Self-paced online course. The course is completed entirely independently by the end of the course deadline. You will study the material in an online learning environment, which includes study materials and assignments/tests. No personal feedback will be provided on the assignments.

Employer connections

Course has been produced in corporation with Osaango Oy. Lecturers on the videos are experts in data economy.

Exam schedules

The course workspace will remain open until the end of the course deadline (see Timing), and all assignments must be completed before the workspace closes.

International connections

The course is offered to partner institutions and its content is designed to be suitable for both EU countries and internationally.

Completion alternatives

-

Student workload

1 ECTS credits = 27 hours of work

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