Örebro University

A close link between education, research and collaboration is the starting point for all our activities. We offer a wide range of attractive professional programs, in medicine, psychology, law and engineering. Our vision is to be a prominent university for a knowledge-driven society.


Autonomous Robots and ROS

ROS (Robot Operating System) is a common set of tools used in academia to do research within autonomous systems. It shortly provides a middleware for handling communication, as well as interfacing sensors and actuators, visualization, simulation and datalogging and infrastructure where it is easy to share your own methods and algorithms. The latter has allowed a large set of different of state-of-the-art research approaches to be readily available for downloading. Due to its popularity it is also getting more widespread in the industrial community, especially in R&D. This course will give you hands-on experience how to utilize these tools and apply them to a problem of your choice.

Data Mining

Nowadays, a hot topic among industrial companies is using AI and deep learning. However, there is a lack of dealing with the collected data to define an appropriate problem statement before creating any advanced AI model. Data mining is the field of discovering novel and potentially useful information from large amounts of data, by exploring the characteristic features and extracting hidden patterns. In the Data Mining course, we aim to cover the most applicable topics of understanding the data, from exploratory data analysis (such as preprocessing, visualization, and statistical techniques) to pattern recognition approaches (such as association rule mining, anomaly detection and clustering).

Declarative Problem Solving with Answer Set Programming

Answer Set Programming (ASP) is a declarative programming paradigm designed within the field of Artificial Intelligence (AI), and used to solve complex search-problems. The declarative nature of ASP allows one to encode a problem by means of logic. In this way, unlike in imperative programming approaches, there is no need to design an algorithm as a solution for the given problem. In this sense, ASP is comparable with SAT-based encoding or constraint satisfaction problems. However, due to its stable-model semantics, ASP provides a richer representation language useful to handle uncertain situations more effectively for real world scenarios. The advantages of declarative programming together with non-monotonic nature of ASP in handling uncertainties have recently made ASP more attractive both for academia and industry. This course focuses on formalizing and solving various search problems in planning, scheduling and system configuration in ASP.

Reinforcement Learning part 2

Reinforcement Learning (RL) is a type of machine learning technique that enables an agent to learn in an interactive environment by trial and error using feedback from its own actions and experiences. The course is part of the education initiative Smarter at Örebro University. This is course requires completion of course Reinforcement Learning part 1.  Read more