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
- Business administration 2023 - 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
- International business 2023 - Business insight management - advanced studies
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
In this study unit the focus lies on the following
competencies:
Fact-based Decision Making Competence
Resilience Competence
Technological Competencies
Leadership
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
Upon completion of this study unit:
You are able to ask managerial
questions that can be answered through the use
of AI methods based on machine learning.
(Knowledge)
You have 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. (Knowledge,
Approach)
Course contents
Machine learning contents for:
-classification
-regression
-natural language processing
-business opportunities with AI methods
-basic knowledge how several AI methods work
Prerequisites and co-requisites
20 credits from your subject module.
Additional information
Have to pass the Mooc course Introduction to AI with
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 Introduction to AI with 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 Introduction to AI with
Elements of AI @ HU.
Teacher
Mohammadi Nafiseh
Examiner
Fabricius Susanna
Home page of the course
Group size
No limit
Assignments valid until
12 months after course has ended
Assessment methods
Date will be announced later - Reports and productions