Programme covers a range of timely, industry topics relevant to modern fields of engineering, comprising competences from electrical engineering, automation, programming, communications, data science, artificial intelligence and machine learning, network security and Internet of Things.

Students will acquire competences in a range of techniques covering the broad areas of mathematics, modelling and analysis of signals and systems, electronics, data science, artificial intelligence, security, networks and distributed systems.

During their studies, students will further acquire expertise in other areas, such as project planning and management, teamwork and coordination, entrepreneurship, critical thinking and sustainability. The Programme will empower students to solve industry-relevant problems employing cutting-edge tools of artificial intelligence, automation and control theory, data analytics, network security, wireless systems, distributed systems and signal processing. Students will be trained in the design and analysis of machine learning models and communication systems, advance their knowledge in the broad field of computer networks and cybersecurity, and gain professional experience through tailored industry-relevant projects and entrepreneurship trainings.

The expertise gained through the Programme features diverse programming skills, good mathematical background, goal-oriented problem solving, as well as efficient project planning and management. 

In particular, students will boast competences in:

• emerging communication technologies: students will learn from experts in the domain of communication and networking;
• cutting-edge automation competences: the Programme boasts theoretical skills and practical expertise at the interconnection between communications and data science;
• emerging information technologies: students will learn from experts in evolving information technologies that define the future in industry and society;
• network security: security is the weak spot in many contemporary technologies, so students will learn to lead the transition of the industry towards security and privacy by design and by default in all types of networks, and more specifically in IoT;
• distributed computer networks: distributed systems have become the norm and are ubiquitously deployed through IoT, so students will learn to command the tools to manage future distributed networks of an unprecedented scale;
• artificial intelligence in networking: data science has found its place in many areas of engineering in recent years and is increasingly dominating also networking domains, students being trained to possess a broad range of tools to structure and analyse huge data sets and to extract meaning from patterns, as well as to appreciate the value created by collecting, communicating, coordinating and leveraging the data from connected devices;
• programming skills: students will gather practical programming expertise in a range of industry-relevant languages;
• project and team working: students will collect practical experience through projects in relation with industry.

First year

First year

Second year

Students are required to complete a Master's thesis, which is a research assignment with a workload corresponding to 30 credits. The thesis is written on a topic usually related to the student's major and agreed upon between the student and a professor who specializes in the topic of the thesis. The supervisor of the thesis is a professor or university lecturer at Aalto University. The thesis advisor(s) can be from a company or from another university. The thesis advisor(s) must have at least a Master’s degree.

Master’s thesis work includes a seminar presentation or equivalent presentation. The student is also required to write a maturity essay related to the Master’s thesis.

The Master’s thesis is a public document and cannot be concealed.

See also Thesis tab.