Applications 2023-02-15 - 2023-08-13
The course addresses fundamental questions related to how to build trusted systems. The focus will be on specific characteristics and approaches that allow to build trust into systems. In addition, methods to ensure that computers and services behave faithfully to the implementation specifications will be presented as well as approaches for detecting malicious deviations from the specifications. This course also introduces Blockchain concepts, security perspective of blockchain, consensus in blockchain, the decentralized philosophy behind Blockchain, as well as the main discussions in Blockchain environment and its potential applications.
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.
The rapid development of digital technologies and advances in communications have led to gigantic amounts of data with complex structures called ‘Big data’ being produced every day at exponential growth. The aim of this course is to give the student insights in fundamental concepts of machine learning with big data as well as recent research trends in the domain. The student will learn about problems and industrial challenges through domain-based case studies. Furthermore, the student will learn to use tools to develop systems using machine-learning algorithms in big data.
The aim of this course is to provide participants with the principles behind model-driven development of software systems and the application of such a methodology in practice. Modelling is an effective solution to reduce problem complexity and, as a consequence, to enhance time-to-market and properties of the final product.
Modern web applications can often be described in terms of cooperation and sharing, both on the level of the users of the application and on the level of the application and the service providers. This course covers the most prevalent security challenges of web applications, from a theoretical and practical perspective.
The course will give insights in fundamental concepts of machine learning and actionable forecasting using predictive analytics. It will cover the key concepts to extract useful information and knowledge from big data sets for analytical modeling