Major code: SCI3020

Entry points: Aalto, Royal Institue of Technology (KTH), University Paris-Sud (UPS), University of Twente (UT), Technical University of Madrid (UPM) and Polytechnic University of Milan (POLIMI).

Exit points with specializations:
Aalto: Computational Interaction
KTH: Mobile and ubiquitous interaction
UPS: Situated interaction
UT: Intelligent systems
UPM: Accessible and Adaptive Interaction
Technical University Berlin (TUB): Multi-modal interaction
University of Trento (UNITN): Cognitive Interaction

Professor in charge:

Marko Nieminen

Other professors of the major:

Perttu Hämäläinen


Antti Oulasvirta


Tapio Takala

Academic coordinator:                             

Mika P. Nieminen

Objectives of the programme

Human Computer Interaction and Design (HCID) focuses on the study, design, development and evaluation of novel user interfaces and interactive systems taking into account human aspects, at the cognitive and sensory-motor levels, technological aspects, as well as business aspects.

New ICT technologies are transforming our daily lives. Smart devices (mobile phones, PDAs, tablet computers), smart products (car, navigation) and smart environments (ambient intelligence) are enabling new services such as navigation, information providing, learning, making reservations or buying of goods are delivered.

Increasingly, the interaction with these devices is not through simple buttons or keystrokes but with more flexible and intuitive interaction methods such as multi-touch, speech, gestures, and with advanced display systems such as augmented and virtual reality. Smart devices and services are also able to show intelligent behaviour recognizing intentions of the user and anticipating the user’s needs. These technologies are central in Human-Computer Interaction and Design.

The design of intuitive user interfaces, however, is not only a matter of the right technology but also a matter of good interaction design: study user’s social and cognitive behaviour in relation to using technology, taking the user as a central driver for design, designing for the right user experience, andtesting and evaluating the design within context, are keys to understanding and designing successful user experience.


Compulsory major courses (11 ECTS)

CodeCourse nameCredits
SCI-E1010Introduction course for Master's students: Academic skills1 ECTS

CS-E4900

User-Centered Methods for Product and Service Design

5 ECTS

Select one of the following courses:

CS-E5220

User Interface Construction

5 ECTS

ELEC-E7851

Computational User Interface Design

5 ECTS


Compulsory I&E Courses (16 ECTS)

CodeCourse nameCredits

CS-E5120

Introduction to Digital Business and Venturing

3 ECTS

CS-E5130

Digital Business Management

4 ECTS

TU-E4100

Startup Experience

9 ECTS


Elective major courses - Select at least 2 ECTS over the two semesters.

Autumn courses:

CodeCourse nameCredits
CS-C3120Human-Computer Interaction5 ECTS

CS-E3210

Machine Learning: Basic Principles 

5 ECTS

CS-C3100

Computer Graphics

5 ECTS

CS-E4400

Design of WWW services

4 ECTS

ELEC-E7890User Research5 ECTS
CS-E4450Explorative Information Visualization5 ECTS
CS-E50xxSeminars and Special courses in Software and Service Engineering5 ECTS

Compulsory major courses (23 ECTS)

CodeCourse nameCredits

LC-xxxx

Language course: Compulsory degree requirement,
both oral and written requirements

3 ECTS

CS-E5200

Design Project

10 ECTS

CS-E5210

Usability Evaluation

5 ECTS

CS-E4200

Emergent User Interfaces

5 ECTS


Compulsory I&E Courses (8 ECTS)

CodeCourse nameCredits

CS-E5140

Global Business in the Digital Age

4 ECTS

CS-E5430

ICT Innovation Summer School

4 ECTS


Elective major courses - Select at least 2 ECTS over the two semesters.

Spring courses:

CodeCourse nameCredits

CS-E4840

Information Visualization

5 ECTS

CS-E4800

Artificial Intelligence

5 ECTS

CS-E5520Advanced Computer Graphics5 ECTS
CS-E50xxSeminars and Special courses in Software and Service Engineering5 ECTS


Total for the whole year: 60 ECTS

Note for exit year at partner university: According to Finnish legislation, a master's thesis is a public document and its contents cannot be confidential. Therefore, the material of the thesis must be chosen so that it does not include any information that could be classified as a business secret of the financing company.

Aalto specialization – Computational Interaction

Aalto University offers a specialisation in Computational Interaction. Students learn to apply methods from computer science, engineering, and mathematics to inform understanding of human-computer inter-action and to design and adapt human-computer interfaces. Such methods build on for instance machine learning, optimisation, statistical modelling, natural language processing, control theory, signal pro-cessing and computer vision, among others. Emerging application topics include computational and data-driven design, interactive AI, conversational agents, interactive visualisation, cognitive and behavior-al modeling, and novel user interface technology.

The specialisation is offered by the Aalto University School of Science and the Aalto University School of Electrical Engineering and it builds on internationally recognized research and education in human-computer interaction, computational intelligence in games, and advanced machine learning methods.


Compulsory major courses (14 ECTS)

CodeCourse nameCredits
SCI-E1010Introduction course for Master's students: Career and working life skills1 ECTS

 LC-xxxx

Language course: Compulsory degree requirement,
both oral and written requirements

3 ECTS

CS-E3210

Machine Learning: Basic Principles*

5 ECTS

ELEC-E7851Computational User Interface Design5 ECTS


Compulsory I&E Courses (6 ECTS)

CodeCourse nameCredits

CS-E5425

I&E Study Project

6 ECTS


Elective major courses (10 ECTS)

CodeCourse nameCredits
DOM-E5129Intelligent Computational Media**5 ECTS
CS-E4840Information Visualization**5 ECTS
ELEC-E7890User Research5 ECTS
ELEC-E7870Advanced Topics in User Interfaces3 ECTS

Only one course of the following can be included in the electives:

CS-E4890

Deep Learning

5 ECTS

CS-E4600

Algorithmic Methods of Data Mining

5 ECTS

ELEC-E8125Reinforcement learning5 ECTS

* If machine learning basics have been studied at entry, select more electives on agreement with academic coordinator.

** Course currently offered during spring semester.


Total: 30 ECTS

CodeCourse nameCredits

CS.thes

Master’s Thesis

30 ECTS


Total for the whole year: 60 ECTS