Master of Science in
Computer Science

The specialisation in Algorithms teaches you to formulate practical problems with algorithmic terms and find new computational solutions. Algorithmic skills are typically desired by large multinational IT brands, and by small innovative start-ups developing new technologies. 
 

Courses: 

1. Linear Algebra and Probability (7.5 ECTS): The course will focus on linear algebra and probability/statistics. 
2. Advanced Algorithms (15 ECTS): The course teaches advanced algorithm design methods, with special emphasis on randomized and algebraic approaches, and parallel algorithms. These approaches are used e.g. in many state-of-the-art algorithms and data structures for handling large data sets, in machine learning, in addressing communication bottlenecks, and in algorithms for computationally hard problems.

The specialisation in Data Systems gives you a thorough understanding of design, analysis, implementation and evaluation of computer systems.

Courses: 

1. Computer Systems Performance (7.5 ECTS): This course covers advanced topics in modern hardware and operating systems to give you a thorough understanding of the potential root causes of performance problems, as well as instrumentation techniques and benchmarking to give you the tools to evaluate system performance in practice.
2. Advanced Data Systems (15 ECTS): This course gives you a thorough understanding of the principles, techniques and algorithms involved in building, maintaining and improving a data system. The course covers in depth issues related to storage management, query processing, and transaction management. You build an open-source data system in the context of this course.

The specialisation in Security teaches you to analyse the security of an IT-system and it gives you a thorough understanding of the construction of ‘secure’ software.

Courses: 

1. Cryptography (7.5 ECTS): This course brings you up to the cutting edge in applied information security, i.e., the technologies currently defining information security in industry. The course comprises both hands-on and foundational learning activities.
2. Advanced Security (15 ECTS): This course studies advanced topics in computer security, principally methods for construction of secure software and systems, generally in the intersection between research topics and applications. The course comprises both practical and foundational work.

The specialisation in Machine Learning gives you both a practical and theoretical understanding of the current field of machine learning as well as a survey of some main areas of application. You will learn to use methods from artificial intelligence and machine learning while working with big data.

Courses: 

1. Linear Algebra and Probability (7.5 ECTS): The course will focus on linear algebra and probability/statistics.
2. Advanced Machine Learning (15 ECTS): In this course, you will learn to derive, analyse and compare the most central machine learning algorithms and, in doing so, their appropriate application to real datasets. You will both carry out the implementation of algorithms and integrate standard packages into their model development. You will apply the learned techniques across an array of applications; possible applications include robotics, image analysis, finance, natural language processing, bioinformations, and business.

The specialisation in Robotics gives you an understanding of the construction of software for robots and you will learn to construct small physical and mechanical artefacts.

Courses: 

1. How to make almost anything (7.5 ECTS): The course is a hands-on introduction to the tools that are necessary to design and develop physical artefacts. The course gives an overview of the most important manufacturing methods like 3D printing, NC milling, laser cutting or moulding. In addition, you will learn how to design simple electric circuits to handle sensors and actuators and how to design printed circuit boards. These techniques will allow you to design physical prototypes on your own at the end of the course.
2. Advanced Robotics (15 ECTS): This course teaches the predominant paradigms in artificial intelligence in the context of robotics: deliberative, behaviour-based, and embodied. The course will introduce a number of advanced topics, e.g. robot learning, evolutionary robotics, swarm robotics, multi-robot coordination, modular robots, simultaneous localisation and mapping. These topics are useful in the context of service robotics, self-driving cars, drones, and other developing robot technologies.

The specialisation in Software Analysis teaches you to use functional programming techniques.

Courses:

1. Modelling Systems and Languages (7.5 ECTS): This course introduces modeling languages and models as first class artifacts that are designed, manipulated, transformed and translated to code in an automatic fashion.
2. Advanced Software Analysis (15 ECTS): This course concerns advanced software verification techniques.

The specialisation in Software Engineering enables you to work as a software engineer and, after gaining industrial experience, provide the base to take over roles as project manager or technical lead. The specialisation will not only introduce you to current software engineering methods and practices, but also enable you to relate to future technical as well as to methodological developments.

Courses:

1. Software Architecture (7.5 ECTS): The design, development, and implementation of software system requires the evaluation of several, often conflicting, aspects of the system. The aim of this course is to provide you with knowledge on how to develop software systems in a structured and systematic way that addresses the required functionality and supports the necessary system qualities. This requires a technical toolbox with concepts, methods, and principles to support the software design, implementation, and evaluation as much as a wider understanding of the context and domain of the system.
2. Advanced Software Engineering (15 ECTS): The purpose of this course is to give you a thorough understanding of innovative processes, methods, and tools for software engineering as well as an introduction to a number of theoretical concepts that allow you to reflect on how methods, processes, and tools support software engineering as a cooperative activity. This way the course enables you to embrace future methodological developments. The course combines theoretical reflection of software engineering and hands-on development of tooling and development of infrastructures, as they e.g. are necessary for continuous software engineering.