DESIGN FOR EXTENDED REALITIES

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 course aims to provide students an opportunity to develop skill in experience design and design thinking. The Usability and User Experience course focuses on the design process, techniques and methods to design and produce digital artifacts with desirable experiential qualities.

The course begins with an introduction to optimization-driven design and how it is used in industrial contexts, this is followed by solution methods for optimization problems in a variable. These introductory parts of the course deal with unlimited optimization and the focus is on creating a variety of solution methods for different types of optimization problems. Examples of solution methods that are treated are linear programming (LP), Newton's method, secant methods and the steepest descent method. In these latter methods, problems are considered in several variables, which also applies to the remaining parts of the course. For limited optimization problems, different methods for handling coercion are presented, for example Karush-Kuhn-Tucker (KKT), quadratic programming (QP), active quantities and multipliers. The course continues with convex optimization and variation differences with application in mechanical engineering and ends with structure, shape and topology optimization. After completed course the student should be able to:show familiarity with basic optimization algorithms and their use,display knowledge about how structural and design optimization can be used during the design process,demonstrate comprehension of how optimization driven design is used in the development of sustainable products,demonstrate the ability to use topology optimization in structural analyses,demonstrate the ability to perform sensitivity analyses,demonstrate the ability to perform a major optimization driven design project.  

According to the OWASP about 75% of vulnerabilities are actually application related. However, the consideration of security aspects during the various phases of software development is still in its infancy in many organizations and the potential of security by design to build high-quality software components is not exploited. Therefore, this course provides software project managers, product owners or software architects with knowledge and skills on how to successfully integrate and continuously improve security practices in traditional and agile development processes. It teaches how to assess and apply security practices in a risk-based way during the analysis, design, implementation, verification, and operation of software products, systems and services in all types of organizations.

ADDITIVE MANUFACTURING: CONCEPTS, METHODS, APPLICATIONS This course comprises all the fundamental elements in the field of Additive Manufacturing (AM). The course focuses on AM’s dynamics and unique characteristics which have the potential to be utilized as a feasible production system both as a standalone technology or in combination with conventional technologies for industrial manufacturing purposes. Basic introduction, various technological classes (as defined by ASTM standard), workflow, design, and applications of AM technologies are among the subjects that are going to be covered during this course. This course aims at establishing a comprehensive knowledge base within the concept of Additive Manufacturing. The course includes the following elements: Definition of basic concepts, introduction of technologies, advantages and limitations of additive manufacturing Classification of technologies, main characteristics, and applications Cataloguing workflow by covering steps from CAD generation to manufacturing and post-processing Comprehension of design for AM (DFAM) and its implications for manufacturers Exploration of applications and value propositions through studying business cases