SECURE SOFTWARE ARCHITECTURE

This course provides an understanding of automating software testing using program analysis with the goal of intelligently and algorithmically creating tests. The course covers search-based test generation, combinatorial and random testing while highlighting the challenges associated with the use of automatic test generation.

This course will teach you how to build convolutional neural networks. You will learn to design intelligent systems using deep learning for classification, annotation, and object recognition.

This course deals with model-based testing, a class of technologies shown to be effective and efficient in assessing the quality and correctness of large software systems. Throughout the course the participants will learn how to design and use model-based testing tools, how to create realistic models and how to use these models to automate the testing process in their organisation.

In this course you will learn state-of-the-art statistical modelling for the purpose of analysing industrial data. The course also presents the basics of relational databases and data manipulation techniques needed to prepare the data for analysis.

This course makes you acquainted with the concept of systems-of-systems (SoS), which means that independent systems are collaborating. It gives you an understanding why SoS is an important topic in the current digitalisation and provides a theoretical and practical foundation for understanding important characteristics of SoS. It also gives you a deeper knowledge in a number of key concerns that need to be considered when engineering SoS. Admitted students to this course may join the course any time between August 28 and October 6, 2023. With the recommended study pace of 25%, the course would take approximate seven calendar weeks to complete. Higher or lower study pace is possible as long as the course is finished no later than January 14, 2024.

Örebro University is offering a course in machine learning. The course will offer knowledge of the basic concepts with machine learning, the selection and application of different machine learning algorithms as well as evaluation of the performance of these learning systems. After completing the course, student should be able to prepare data and apply machine learning techniques to solve a problem in an intelligent system. The course is part of the education initiative Smarter at Örebro University.