Master degree

Computer Engineering

The Master's in Computer Engineering will give you insight into the theory, methods and tools of computer engineering. The programme focuses on computer systems, cloud-based technologies, advanced machine learning and generative AI, big data processing and analysis and cybersecurity. You will be part of an international educational and research environment where you will gain access to the latest knowledge and technology while working with technologies at the forefront of digital development.

Copenhagen

Where

English

Language

2-year education

Master degree

September

Study start

Apply for admission

Master degree

Computer Engineering

Copenhagen

Where

English

Language

2-year education

Master degree

September

Study start

Apply for admission

About the programme

You should choose Computer Engineering if you want to design and implement scalable, robust and efficient cloud-based solutions. If you want to understand the possibilities in being able to manipulate and analyse large amounts of data. And if you want to learn how we can use advanced algorithms to create intelligent, impactful solutions that make a difference in society and the world at large.

Educational content

While pursuing your degree, your schedule will alternate between lectures and project work in groups where you and your fellow students develop IT solutions for concrete problems, such as optimising energy consumption in cities, improving healthcare data, or developing intelligent systems for industry, to name a few. Along the way, you will receive feedback and support from dedicated professors who are experts in their fields and in on the latest research and technology. You will also have the opportunity to collaborate with companies. The programme is conducted in English.

Your skills as a graduate

Job opportunities

With a Master's in Computer Engineering, you get a strong and international technical profile. Your skills will be in high demand in both Danish and international companies – small, medium and large – and in public organisations where you can develop solutions within the analysis, design and implementation of computer systems that incorporate cloud integration, big data processing systems and high-performance computing. Some graduates choose to stay at university to pursue a three-year research programme (PhD).

Join AAU's online Master's Fair

Would you like to learn more about this master's programme? Join AAU's online Master's Fair on December 11

New Master’s options

We expect that as of 2028 you will be able to take this Master's degree programme as a 2-year programme (full-time study, 120 ECTS credits) and as a 3-year Master's for working professionals (first year full-time and then two years of part-time study in combination with relevant employment)

Learn more about your new master’s options at AAU

The Master's programme in Computer Engineering offers a variety of options that allow you to specialize in different areas. During the four semesters, you both take courses and do projects.

Programme structure

Semester overview

Courses and projects

The courses provide you with the knowledge, tools and competencies to work with methods and theory within a specific area, while the project modules give you and your fellow students the opportunity to work in an interdisciplinary way in a problem-oriented context where the knowledge, tools and competencies are put to use. In the projects, you will work on real-world issues in close collaboration with both Danish and international companies and institutions. This gives you the opportunity to build experience and competencies for your future career.

1st semester

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.

2nd semester

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.

3rd semester – project at AAU or project-oriented course (internship) in a company

In the third semester, you must take the compulsory course:

Data Mining and Analysis (Course module, 5 ECTS credits)
This course provides a systematic approach to solving problems with large and/or dispersed data sets. Based on concepts such as big data and data lakes, you learn techniques for extracting, loading and transforming data from different sources. Emphasis is placed on analysis and insight into data that can optimize and drive the operation of exemplary systems. Finally, the course covers the principles of data visualization so that results can be presented effectively and support decision-making in practice.

In addition, you can choose one of the following two options:

1. Project-oriented course (internship) in a company or organization in Denmark or abroad

You can choose to do a project-oriented course (internship) in a public or private organization or company. This option gives you the opportunity to test theoretical skills and methods in practice and gain concrete experiences that can provide inspiration for your studies and Master’s thesis. You must have a learning objective for the course, and you must ensure that the tasks you solve are academic in nature. The project-oriented course (internship) can be in Denmark and abroad.

2. Project module and elective course

If you choose this option, you must follow the third semester's project module and one elective course.

You must chose one of the following project modules:

Big Data Engineering in Practice (Elective project module, 20 ECTS credits)
The project blends theoretical and practical work on a chosen problem that deals with big data computing for e.g. IoT (smart homes, smart energy), Industry 5.0 (smart factories), social networks or network security. In the project, you and your fellow students analyze a chosen problem and break it down into sub-problems that can be solved using methods and theories on, for example, distributed systems, data mining and machine intelligence – and, finally, demonstrate the functional solution.

Sustainable ICT Solutions (Elective project module, 20 ECTS credits)
The project module deals with digital transformation and sustainability. You can focus on either sustainability in digitalization and digital systems or digital transformation where the use of digital technologies paves the way for sustainability in other sectors. The project module is about socio-technical choices and priorities in digital transformation and sustainability. You work on analyzing specific examples of digitalization that have both opportunities and barriers for further digital transformation and sustainability – and that provide you with knowledge on the importance of developing sustainable guidelines for digital transformation in the future.

And you must chose one of the following courses:

Quantum Technologies (Course module, 5 ECTS credits)
The course is an introductory course to the theoretical and practical basis and use of quantum technology. It covers topics such as mathematical fundamentals of quantum theory, quantum computer architecture, quantum algorithms, optimization and computational acceleration, security, and quantum communication.

Network Security (Course module, 5 ECTS credits)
The course gives you a thorough introduction to network monitoring and network security – both passive methods for network monitoring and network analysis and active methods such as network scanning. You gain knowledge on the most important network-based IT security threats such as botnets, security protocols in general and more specifically for wireless networks and security challenges when setting up networks (configurations and equipment) and general knowledge on tracking malicious network activities.

Programming Paradigms (Course module, 5 ECTS credits)
The course provides you with knowledge, skills and competencies in basic mathematical disciplines that are important in many computer science contexts – e.g. when working on algorithms, data structures and software development.

Web Intelligence (Course module, 5 ECTS credits)
The course provides you with knowledge and skills in web intelligence techniques and covers topics such as: web agents and web services, web information retrieval, web navigation support, recommender systems, intelligence for social web, knowledge representation, user modelling, adaptation and personalization, and applications of web intelligence techniques.

Industrial Test and Verification (Course module, 5 ECTS credits)
The course provides you with knowledge and skills in software testing and verification. The course covers topics such as classical testing techniques and test theory, test specification, models for formal testing and model-based testing, software tools for automated testing, test generation and test execution, formal models of software system behaviour, software tools for verifying models – and as part of that, the techniques: static analysis, model checking, bounded model checking, quantitative model checking, challenges and examples of how verification can be scaled to industrial applications.

4th semester

Option to study abroad

Curriculum

Skills and job opportunities

Get help at AAU to start your career in Denmark

AAU Career helps you on your way from student life to job life in Denmark by giving you the tools to examine your options and find out what to do.

While studying at AAU, you can participate in career and job-related events, find help on our website, and book a personal career counselling session to talk about e.g.:

Finding your way in your career
Danish working culture
Application and CV the Danish way
What you can offer an employer
How to go about job search in Denmark – both student job, internship and full-time job