The course is included in these curricula and study modules
- International business management - a nordic focus 2016 - Financial technology (fintech)
- International business management 2017 - Financial technology (fintech)
- International business management 2019 - Financial technology (fintech)
- International business management 2020 (part-time) - Financial technology (fintech)
- International business management 2020 (full-time) - Financial technology (fintech)
- International business management 2021 (full-time) - Business development, digitalisation and fintech - specialised professional studies
- International business management 2021 (part-time) - Business development, digitalisation and fintech - specialised professional studies
- International business management 2022 (part-time) - Business development, digitalisation and fintech - specialised professional studies
- International business management 2022 (full-time) - Business development, digitalisation and fintech - specialised professional studies
- International business management 2023 (full-time) - Business development, digitalisation and fintech - specialised professional studies
- International business management 2023 (part-time) - Business development, digitalisation and fintech - specialised professional studies
The course takes place in period
3 (2023-01-01 to 2023-03-19)
Level/category
Teaching language
English
Type of course
Compulsory
Cycle/level of course
Second
Recommended year of study
1
Total number of ECTS
5 cr
Competency aims
In this study unit the focus will for you to build
the following competences:
- Competence in digital transformation of the
business landscape
- Competence in the foundations for AI & machine
learning, analytics
Learning outcomes
After completing the study unit, you:
- can discuss new business models and business
activities that emerge through changes in
legislation and the introduction of new
technologies.
- understand the opportunities created by AI and
machine learning
- understand the limitations of AI and machine
learning
- understand how AI and machine learning can be
utilized to develop existing processes and build
new business models
Prerequisites and co-requisites
A bachelor degree and at least two years work
experience gained after completing the higher
education degree.
Previous course names
Fintech and Data Analytics
Study activities
- Lectures - 25 hours
- Individual studies - 110 hours
Workload
- Total workload of the course: 135 hours
- Of which autonomous studies: 135 hours
- Of which scheduled studies: 0 hours
Mode of Delivery
Participation in tuition
Assessment methods
Essays, reports, productions and portfolio
Teacher
- Nyman Henrik
- Olmedilla Fernández María
Examiner
Nyman Henrik
Home page of the course
Group size
No limit (22 students enrolled)
Assignments valid until
12 months after course has ended
Course enrolment period
2022-12-10 to 2023-01-12
Assessment methods
Date will be announced later - Reports and productions
| Date | Time | Room | Title | Description | Organizer |
|---|---|---|---|---|---|
| 2023-04-11 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María | |
| 2023-04-12 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María | |
| 2023-04-13 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María | |
| 2023-04-14 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María | |
| 2023-05-02 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María | |
| 2023-05-03 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María | |
| 2023-05-04 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María | |
| 2023-05-05 | 16:30 - 20:00 | B522 | Artificial Intelligence | Olmedilla Fernández María |