Computer vision is about teaching computers to understand and interpret visual information based on data from images and videos. The study line course will teach you how to use fundamental concepts and techniques such as pattern recognition and deep neural networks, and you will gain an understanding of the algorithms and mathematics behind machine learning, image processing and object recognition.
In many ways, computer vision has been a driving force behind the development of artificial intelligence in recent years, and computer vision will undoubtedly be crucial to many of the technological leaps in the digitalisation of society that we will see in the coming years. The study line course will therefore provide you with a number of opportunities in your future career.
You will learn to work with both hardware and software on the study line course in Embedded Systems.
You will gain a theoretical understanding of what it is like to work with real-time systems that are dependent on precision and fast responses. Through practical exercises and projects, you will learn to develop different types of embedded systems that can handle the demands of drones, medical devices, modern industrial production, etc. You will also learn how to work with reliability and security in critical systems, so that once you graduate, you will have competencies within both modelling and software development at an advanced level, where failures can have serious consequences for aircraft, cars, space technology, energy networks, etc.
Embedded systems are a core discipline within computer engineering, and your Master's degree will ensure that you are in high demand by virtually every industry.
As a student on the study line course in robotics, you will learn about advanced robotics technologies. You will increase your theoretical knowledge of machine learning, software and advanced control systems, and you will work on programming and designing robots to act autonomously and intelligently, and to solve the tasks you define for them.
The study line course works with all kinds of robots, including drones, which you can fly in our large drone hall at AU’s Deep Tech Experimental Hub in Skejby.
Robotics is a cross-disciplinary engineering discipline, and you will have plenty of opportunity to supplement the programme with elective courses at the Department of Mechanical and Production Engineering if you want to strengthen your engineering profile within mechatronics, for example.
This study line course builds on what you have already learned about software development and software architecture. You will gain a deep theoretical understanding of the mathematics behind programming and learn more about the fundamental engineering principles needed to tackle highly complex software challenges.
You'll have an opportunity to delve into topics such as declarative programming and software correctness, which will enable you to develop software and systems that meet specific requirements and that can perform tasks flawlessly. You will also learn about databases, data management, digital twins and cyber security.
Once you graduate, you will be in high demand by the labour market, and you will be able to use your software knowledge in many different jobs within many different sectors.
As a student on the study line course in Times Series Signal Processing, you will learn about both stochastic and advanced signal processing. You will learn to analyse and manage data that can be measured or observed as points collected in time intervals. For example, time series of sensor data, financial data, medical data, weather data and much more.
You'll gain a general understanding of the mathematics behind signal processing, learn how to detect and process noise and use deep learning to spot unusual events in time series. You'll work with cases and apply your knowledge in a variety of contexts such as predicting rainfall, diagnosing diseases or detecting share-price manipulation. This means that, as a student, you will already begin developing an idea of the innovation needs and opportunities of different sectors in modern signal processing.
Once you graduate with an MSc in Engineering, you'll be able to use your knowledge to make smart decisions based on both historical and current time-dependent data, and you'll be very sought after by a number of sectors.
As a student on the study line course in Wireless Networks, you will learn about wireless communication networks, systems, network protocols and network mechanisms. You will learn the theory behind a number of the communication technologies that make it possible to send data efficiently in terms of energy and resources.
You will also gain experience with using different wireless technologies in your work as an engineer, and you'll have an opportunity to delve into topics such as sensor networks and the Internet of Things. You'll also learn to work with computer security, encryption and error detection. This will ensure that once you graduate as an MScEng, you will be able to implement a variety of methods to optimise data integrity and confidentiality while reducing the risk of cyber-attacks and disruptions that can hinder a network's performance.
Wireless networks is a central discipline in modern computing engineering, and they are a fundamental infrastructure for the ongoing digitalisation of society. With a Master's degree in this field, you will be equipped to take on many different types of engineering jobs, within many sectors. Your theoretical foundation will give you a future-proof engineering profile because you will be able to manage the next generation of wireless networks.