Introduction to Data EconomyLaajuus (1 cr)
Study unit code: HY00BT31
Credits
1 op
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
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, Verkkokampus, tiko
Campus
Laurea Virtual Campus
Teaching languages
- English
Seats
0 - 500
Degree programmes
- Complementary competence, master’s studies in English (CYJ2), Generic studies
Teachers
- Essi Tammisto
Teacher in charge
Anssi Mattila
Scheduling groups
- Avoin AMK (Size: 100. Open UAS: 100.)
- Tutkinto-opiskelija tai polkuopiskelija (Size: 0. Open UAS: 0.)
Groups
-
TYJ24SJTäydentävä osaaminen (yamk-tutkinto), S24, yhteiset opinnot
-
CYJ24SJComplementary competence (master’s studies in English), S24, Generic studies
Small groups
- Tutkinto-opiskelija tai polkuopiskelija
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.
Enrollment
27.11.2023 - 19.05.2024
Timing
01.12.2023 - 30.06.2024
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
- Essi Tammisto
Teacher in charge
Anssi Mattila
Scheduling groups
- Koskee vain Avoimen AMK:n asiakkaita, älä ilmoittaudu tähän pienryhmään 1 (Size: 400. Open UAS: 400.)
Groups
-
TYJ23SJTäydentävä osaaminen (yamk-tutkinto), S23, yhteiset opinnot
-
CYJ23SJComplementary competence (master’s studies in English), S23, Generic studies
Small groups
- Koskee vain Avoimen AMK:n asiakkaita, älä ilmoittaudu tähän pienryhmään 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
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
-
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 available only for the master's level degree students and for open UAS students.
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.
Enrollment
22.05.2023 - 30.11.2023
Timing
01.06.2023 - 31.12.2023
Number of ECTS credits allocated
1 op
Virtual proportion
1 op
Mode of delivery
Distance learning
Unit
Korkeakouluyksikkö D, Tikkurila, tiko
Campus
Laurea Virtual Campus
Teaching languages
- English
Seats
0 - 500
Degree programmes
- Complementary competence, master’s studies in English (CYJ2), Generic studies
Teachers
- Niklas Leppä
- Essi Tammisto
Teacher in charge
Anssi Mattila
Scheduling groups
- Avoin AMK (Size: 100. Open UAS: 100.)
- Tutkinto-opiskelija tai polkuopiskelija (Size: 0. Open UAS: 0.)
Groups
-
TYJ23SJTäydentävä osaaminen (yamk-tutkinto), S23, yhteiset opinnot
-
CYJ23SJComplementary competence (master’s studies in English), S23, Generic studies
Small groups
- Tutkinto-opiskelija tai polkuopiskelija
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
-
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 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.
Enrollment
28.11.2022 - 21.05.2023
Timing
01.12.2022 - 30.06.2023
Number of ECTS credits allocated
1 op
Virtual proportion
1 op
Mode of delivery
Distance learning
Unit
Korkeakouluyksikkö D, Verkkokampus, tiko
Campus
Laurea Virtual Campus
Teaching languages
- English
Seats
0 - 500
Degree programmes
- Complementary competence, master’s studies in English (CYJ2), Generic studies
Teachers
- Essi Tammisto
Teacher in charge
Anssi Mattila
Scheduling groups
- Avoin AMK (Size: 200. Open UAS: 200.)
Groups
-
CYJ23KJComplementary competence (master’s studies in English), K23, Generic studies
Small groups
- Avoin AMK
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. Enrolment to this course is ongoing and new enrolments will be handled about once a week.
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 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.
Enrollment
02.07.2022 - 31.07.2022
Timing
01.08.2022 - 31.12.2022
Number of ECTS credits allocated
1 op
Mode of delivery
Contact teaching
Unit
Korkeakouluyksikkö D, Verkkokampus, tiko
Teaching languages
- Finnish
Degree programmes
- New competence and guidance in the software sector and digital skills for beneficiaries of temporary protection staying in Finland
Groups
-
AVOHDK23OODI - Ohjelmistoalan uutta osaamista ja ohjausta sekä digitaitoja Suomessa oleskeleville tilapäistä suojelua saaville
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
Grading scale
Approved/Failed
Enrollment
24.05.2022 - 27.11.2022
Timing
01.06.2022 - 31.12.2022
Number of ECTS credits allocated
1 op
Virtual proportion
1 op
Mode of delivery
Distance learning
Unit
Korkeakouluyksikkö D, Verkkokampus, liko
Campus
Laurea Virtual Campus
Teaching languages
- English
Seats
0 - 500
Degree programmes
- Complementary competence, master’s studies in English (CYJ2), Generic studies
Teachers
- Suvi Valsta
Teacher in charge
Anssi Mattila
Scheduling groups
- Avoin AMK (Size: 100. Open UAS: 100.)
Groups
-
CYJ22KJComplementary competence (master’s studies in English), K22, Generic studies
Small groups
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
-
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
Enrollment
29.11.2021 - 23.05.2022
Timing
01.12.2021 - 30.06.2022
Number of ECTS credits allocated
1 op
Virtual proportion
1 op
Mode of delivery
Distance learning
Unit
Korkeakouluyksikkö D, Tikkurila, liko
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.)
Groups
-
CYJ21SJComplementary competence (master's studies in English), S21, 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
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
-
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