The course is included in these curricula and study modules
- Information technology 2014 - Machine learning and decision support system development
- Information technology 2015 - Machine learning and decision support system development
- Information technology 2016 - Machine learning and decision support system development
- Information technology 2017 - Machine learning and decision support system development
- Information technology 2018 - Machine learning and decision support system development
- Information technology 2019 - Machine learning and decision support system development
- Information technology 2020 - Machine learning and decision support system development
- Information technology 2021 - Machine learning and decision support system development - advanced studies
- Information technology 2022 - Machine learning and decision support system development - advanced studies
- Information technology 2023 - Machine learning and decision support system development - advanced studies
The course takes place in period
1 (2023-08-01 to 2023-10-22)
Level/category
Teaching language
Swedish
Type of course
Compulsory
Cycle/level of course
First
Recommended year of study
4
Total number of ECTS
5 cr
Competency aims
In this study unit we focus on the following
competences:
Machine learning and decision support systems with
focus on:
Responsible and ethical use of machine learning
Recommendation machines
SDG's in focus:
#4: Quality education
#9: Industry, innovation and infrastructure
Learning outcomes
Upon completion of this study unit
You are familiar with techniques being used in
automatic decision support systems. (Knowledge)
You can validate whether an automatic decision is
reasonable or not. (Skills)
You have detailed and holistic knowledge about
problems and challenges related to algorithmic
decision making and how to solve them. (Approach)
Prerequisites and co-requisites
Predictive Analytics
Study activities
- Lectures - 28 hours
- Practical exercises - 30 hours
- Project- and production work/artistic activities - 50 hours
- Individual studies - 27 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
Project and
presentation
Teacher
- Kuvaja-Adolfsson Kristoffer
- Westerlund Magnus
- Karlsson Jonny
Examiner
Westerlund Magnus
Home page of the course
Group size
No limit (25 students enrolled)
Assignments valid until
12 months after course has ended
Course enrolment period
2023-08-10 to 2023-09-06
Assessment methods
Date will be announced later - Other assignments
| Date | Time | Room | Title | Description | Organizer |
|---|---|---|---|---|---|
| 2023-09-04 | 10:00 - 12:30 | F365 | Beslutsstödsystem och verifikation | Introduktion av beslutsstödsystem | Kuvaja-Adolfsson Kristoffer |
| 2023-09-07 | 13:00 - 16:00 | E387 | Beslutsstödsystem och verifikation | Introduktion till beslutsträd | Kuvaja-Adolfsson Kristoffer |
| 2023-09-13 | 12:30 - 15:30 | E385 | Beslutsstödsystem och verifikation | Partiskhet (Bias), Etik och GDPR | Kuvaja-Adolfsson Kristoffer |
| 2023-09-18 | 13:00 - 16:00 | E383 | Beslutsstödsystem och verifikation | Trusthworthy AI som presenterat av överlärare Magnus Westerlund från Z-inspection | Kuvaja-Adolfsson Kristoffer Westerlund Magnus |
| 2023-09-22 | 12:30 - 15:30 | E387 | Beslutsstödsystem och verifikation | Introduktion till Rekommendationssystem | Kuvaja-Adolfsson Kristoffer |
| 2023-09-27 | 12:30 - 15:30 | E385 | Beslutsstödsystem och verifikation | Vetenskaplig fördjupning i rekommendationssystem | Kuvaja-Adolfsson Kristoffer |
| 2023-10-06 | 13:00 - 16:00 | E387 | Beslutsstödsystem och verifikation | Kodtillfälle | Kuvaja-Adolfsson Kristoffer |
| 2023-10-12 | 08:00 - 11:00 | E385 | Beslutsstödsystem och verifikation | Presentationstillfälle | Kuvaja-Adolfsson Kristoffer |
| 2023-10-12 | 13:30 - 16:00 | E385 | Beslutsstödsystem och verifikation | Presentationstillfälle | Kuvaja-Adolfsson Kristoffer |