Customer Satisfaction
Formålet med modulet er, at introducere de studerende for de grundlæggende muligheder og problemstillinger, der er med brugen af Machine Learning og/eller AI i forhold til at måle og forbedre kundetilfredshed. Modulet vil også diskutere de etiske og moralske aspekter af dataindsamling, analysering og brugen af data, der er forbundet med brugen af Machine Learning og/eller AI i forbindelse med Kundetilfredshed.
Modulet giver den studerende:
- Et sprog for AI og indsigt i, hvilke muligheder teknologien giver ifm kundetilfredshed
- Hands-on-experience med opbygning og træning af en relevant AI model (supervised machine learning -> random forest arkitektur
- Indsigt i hvordan omdanner vi data til forretningsindsigt, så vi målrettet kan forbedre/arbejde/beslutte tiltag der kan forbedre kundetilfredsheden
- Indsigt i de etiske overvejelser som særligt vigtige i forhold til indsamling og brug af data i forbindelse med brugen af AI i forbindelse med måling og forbedring af kundetilfredshed. Herunder eksempelvis privacy og udelukkende fokus på kvantitative mål i forbindelse med medarbejderevalueringer.
In English
The purpose of the module is to introduce the student to the basic possibilities and problems that may be associated with using ML and / or AI in connection with Customer satisfaction. Seen from the perspective of decision making, when collecting, analyzing and utilizing data, the module will also discuss ethical and moral aspects connected to the use of ML and/or AI in connection with customer satisfaction.
The module will give the student:
- A language for AI and insight as to which possibilities the technology has in relations to customer satisfaction
- Hands-on-experience with building and training a relevant AI model (supervised machine learning -> random forest architecture)
- Insight into how we transform data to business insights, enabling us to focus on improving/work/decide on ways to improve customer satisfaction
- Insight into ethical considerations as important in relation to collecting and using data using AI when measuring and improving customer satisfaction. Including privacy issues and issues with exclusive focus on quantitative measures in employee evaluations.
The module will give the student:
- A language for AI and insight as to which possibilities the technology has in relations to customer satisfaction
- Hands-on-experience with building and training a relevant AI model (supervised machine learning -> random forest architecture)
- Insight into how we transform data to business insights, enabling us to focus on improving/work/decide on ways to improve customer satisfaction
- Insight into ethical considerations as important in relation to collecting and using data using AI when measuring and improving customer satisfaction. Including privacy issues and issues with exclusive focus on quantitative measures in employee evaluations.
