The course is included in these curricula and study modules
- Business administration 2018 (logistics) - Business insight management
- Business administration 2018 (marketing) - Business insight management
- Business administration 2018 (tourism) - Business insight management
- Business administration 2019 - Business insight management
- Business administration 2020 - Business insight management
- Business administration 2021 - Business insight management - advanced studies
- Business administration 2022 - Business insight management - advanced studies
- International business 2018 - Business insight management
- International business 2019 - Business insight management
- International business 2020 - Business insight management
- International business 2021 - Business insight management - advanced studies
- International business 2022 - Business insight management - advanced 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
First
Recommended year of study
3
Total number of ECTS
5 cr
Competency aims
Competencies
Within this study unit we will focus on the
following competencies:
The aim of the course is that the student knows
common AI methods for analysing historical data.
Another aim is to make student capable of finding
AI opportunities in different business domains in
order to find sustainable solutions through
digital transformation.
SDG?s in focus:
1 NO POVERTY
4 QUALITY EDUCATION
5 GENDER EQUALITY
8 DECENT WORK AND ECONOMIC GROWTH
9 INDUSTRY, INNOVATION AND INFRASTRUCTURE
10 REDUCED INEQUALITIES
12 RESPONSIBLE CONSUMPTION & PRODUCTION
Learning outcomes
The student should be able to ask managerial
questions that can be answered through the use
of AI methods based on machine learning. Student
has a fair understanding of the field of data
science and how business value can be created
through data analysis and thus, contribute to a
more sustainable business environment.
Course contents
Machine learning contents for:
-classification
-regression
-natural language processing.
Prerequisites and co-requisites
20 credits from your subject module.
Additional information
Have to pass the Mooc course Elements of AI @ HU.
Please note that the course Elements of AI cannot be
accredited as extension studies. The course is
included in this course.
Recommended or required reading
Mooc course Elements of AI @ HU and others
Study activities
- Lectures - 20 hours
- Project- and production work/artistic activities - 65 hours
- Internet-based studies - 50 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
Assessment requirements
To pass the course the student must participate
and do the assignments given during the course.
Have to pass the Mooc course Elements of AI @ HU.
Teacher
Björk Kaj-Mikael
Examiner
Björk Kaj-Mikael
Home page of the course
Group size
No limit (39 students enrolled)
Assignments valid until
12 months after course has ended
Course enrolment period
2022-12-26 to 2023-01-05
Assessment methods
Date will be announced later - Reports and productions
Date | Time | Room | Title | Description | Organizer |
---|---|---|---|---|---|
2023-01-10 | 08:30 - 12:30 | B320 | AI for Business | Björk Kaj-Mikael | |
2023-01-17 | 08:30 - 12:30 | B320 | AI for Business | Björk Kaj-Mikael | |
2023-01-24 | 08:30 - 12:30 | B320 | AI for Business | Björk Kaj-Mikael | |
2023-01-31 | 08:30 - 12:30 | B320 | AI for Business | Björk Kaj-Mikael | |
2023-02-07 | 08:30 - 12:30 | B320 | AI for Business | Björk Kaj-Mikael | |
2023-02-14 | 08:30 - 12:30 | B320 | AI for Business | Björk Kaj-Mikael | |
2023-03-07 | 08:30 - 16:30 | AI for Business | Kaj-Mikael Björk is inviting you to a scheduled Zoom meeting. Join Zoom Meeting https://arcada.zoom.us/j/63721933427?from=addon Meeting ID: 637 2193 3427 Join by SIP 63721933427@109.105.112.236 63721933427@109.105.112.235 Join by H.323 109.105.112.236 109.105.112.235 Meeting ID: 637 2193 3427 | Björk Kaj-Mikael |