Complex System Design and Development (Project module, 15 ECTS credits)   
In this project module, you and your group will create a project based on a real problem. For example, you can work on developing and designing scalable web applications, creating distributed systems, implementing IoT solutions that are integrated into the cloud or developing cloud-native applications. The solution’s architecture must have elements of cybersecurity. Along the way, you use the knowledge and skills from the semester's course modules.   
    
Cloud Technologies (Course module, 5 ECTS credits)   
The course focuses on emerging trends and advanced topics in cloud technologies. You will explore cutting-edge developments in cloud computing, including serverless computing, microservice architecture, container orchestration (e.g. Kubernetes), Infrastructure as Code (IaC), DevOps practices, hybrid and multi-cloud strategies, and cloud-native application development. The course emphasizes hands-on experience with advanced cloud platforms and tools that give you the skills to design and implement scalable, robust, and efficient cloud solutions. 
   
Security in IoT and Cloud Architectures (Course module, 5 ECTS credits)   
In the course, you learn about basic practical and theoretical aspects of security in IoT devices and cloud technologies – both security characteristics of IoT devices and systems and security characteristics of virtualization technologies in cloud and edge architectures. You also gain knowledge on privacy and cybersecurity aspects of the business world.  
   
Computer Systems Engineering (Course module, 5 ECTS credits)
The course provides you with competencies to model, analyze, design, implement and validate complex computer systems. You gain knowledge on requirements development, investigation of the solution space (the ability to choose the optimal one based on several criteria), design of the architecture for the chosen solution, reliability, testing and evaluation, maintenance, risk management, etc. of complex projects.  

High-performance Systems (Project module, 15 ECTS credits)   
In this project module, you and your fellow students will work on both the design, implementation and optimization of algorithms for parallel execution on multi-core processors or GPU-accelerated systems, and on the parallelization of applications for distributed computing environments or optimization of performance-critical components in software systems. The project work strengthens your understanding of the underlying principles of high-performance computing, the use of optimization techniques and evaluation of performance measurements in specific systems.   
   
Numerical Scientific Computing (Course module, 5 ECTS credits)
The course provides you with knowledge on principles of parallelization, communication, and data transfer in distributed computing, and on programming techniques, profiling, benchmarking, code optimization, and numerical accuracy in scientific computer problems.   
   
AI and Advanced Machine Learning (Course module, 5 ECTS credits)  
The course provides you with theoretical knowledge of advanced machine intelligence topics, primarily within generative AI and reinforcement learning including single and multi-agent deep reinforcement learning. The course also covers topics such as explainable AI. The theories, methods and techniques are illustrated through concrete practical problems.  
 
Big Data Management (Course module, 5 ECTS credits)   
This course provides you with tools to manage, process, and optimize workflows for large amounts of data. Topics include data lakes, lakehouses, and efficient file formats (e.g., Parquet, ORC), and batch and real-time processing frameworks (e.g., Hadoop, Flink). You learn how to design ETL workflows and implement scalable database systems for unstructured data. A focus on performance optimization and workflow orchestration (e.g., Apache Airflow) prepares you to be able to build scalable big data systems for practical use.  

Master's Thesis (Project module 30 ECTS credits)  
In the last semester, you write your Master's thesis.   

Curriculum for master's programme in Computer Engineering.

With a Master's degree in Computer Engineering, you have an international and strong technical profile. You are skilled in developing solutions in analysis, design and implementation of computer systems with cloud integration, big data computing systems and high-performance computing. You can apply your skills in Danish and international small, medium-sized and large companies and in public organizations where you can solve tasks such as: 

• Computing and composing complex algorithms that can facilitate work on computer-based methods for weather forecasts or financial modelling
• Simulation and modelling for research on e.g. climate science and drug development
• Optimizing customer insights through recommendation systems, sentiment analysis, and user behaviour modelling
• Developing multi-cloud strategies for companies to optimize costs and resilience in their IT infrastructure
• Improving decision-making processes in public services by, for example, collecting and analyzing data from transport or health systems
• Combining big data analysis with AI for urban planning – e.g. for optimizing public transport networks or energy consumption
• Contributing to discussions and decision-making processes on how quantum systems can be utilized to solve complex optimization problems in logistics, finance or engineering 

Aalborg University is famous for its problem based learning which means that you work in a group on a written assignment each semester - possibly in collaboration with an industrial partner. This study method is also called “The Aalborg Model for Problem Based Learning”. The method is highly recognised internationally; including by UNESCO.
The problem based project work at Aalborg University gives you the opportunity to acquire new knowledge and competencies at a high academic level in an independent way. You get to apply theory to practice when you work to solve real-life problems, which will ensure that you are well prepared for your future career.
Learn more about PBL.

When doing project work, you work closely in groups with other students who have roughly the same academic interests and ambitions as yourself. This gives you the opportunity to cooperate, share knowledge and to explore larger and more complex academic problems than you would have been able to do on your own. Furthermore, the groups serve a social purpose and make it easier for you to get to know your fellow students.
Learn more about group work at AAU.

Aalborg University works closely with the business community, which means that during your studies you work with real issues from companies and organisations. Thus, you will already have the opportunity while studying to obtain practical experience with the theory you learn at the university.

At Aalborg University, we offer research-based teaching, which in short means that your lecturers conduct research in the same area they teach. You thus have access to the latest knowledge and dedicated teachers who are passionate about what they teach. The teaching material thus not only includes books but may also consist of current articles from journals. 

The laboratories at Aalborg University are of the highest standard, and they play an important role in the teaching. You will work under the best laboratory conditions with access to state-of-the-art technology, which is vital for your benefiting from the teaching.

As a university city, Aalborg has many advantages. The city is Denmark's fourth largest, and a good 20 percent of the municipality's inhabitants are students. The city has much to offer when it comes to culture, sports and leisure, but at the same time, has a manageable size and safe environment. Compared to other university cities in Denmark, it is easy to find good student accommodation in Aalborg.
Learn more about student life in Aalborg and what it means to study in Aalborg.