Predicting is central to decision-making, but frequently the actual problem is not taken into account. Moving from a descriptive to a predictive context alters the conditions for both methodological and modelling aspects. This course involves providing you with more of an in-depth understanding of the differences and introducing the central modelling families, as well as the details of predictive experimental design.
Predictive modelling should support the user
During this course, we will discuss the aspects of uncertainty, predictability and causality in order to build up more of an understanding of how they affect modelling and analysis. It will become clear during the course that predictive modelling is all about supporting users and decision-makers, and not just creating predictions.
To predict is to stay one step ahead
More specifically, the course will focus on predictive modelling: data analysis and exploration for forecast modelling, extrapolative forecast models, causal predictive models, use of domain expertise and judgement in data-driven predictions, and evaluation of models and predictions.
After completing the course, you will be able to:
- explain the principles of predictive modelling,
- provide support for real-world decision-making and solve predictive problems using different model families,
- design and conduct valid experiments in a predictive environment,
- quantify prediction and modelling uncertainties and map how these connect to supporting users,
- model the limits of predictability and causality and how these can be estimated, and reflect on how these models and methods can be used in your own organisation.
Who is the course for?
This course is aimed at professionals who want to gain more of an understanding of how big data analytics and predictive models can help businesses make better decisions.
Contact wiser@his.se if you are interested in taking this course.
Course format
The courses in their educational form and scope are intended to be combined with work. This means that all courses are:
- Online
- Short courses (3 ECTS)
- Has a study rate of 20% (equivalent to approximately 8 hours a week for 10 weeks)
- Conducted through self-study as well as occasional scheduled occasions where you get the opportunity to meet other course participants and the course's teachers (these meetings are conducted remotely via Zoom).
The KK Foundation
The course is developed within the WISER project. We offer tailor-made courses for digital transformation and are aimed at professionals. The project is co-financed by the KK foundation within the framework of Expert competence. For more information visit: his.se/wiser