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Master's Programme in Computer, Communication and Information Sciences
Curriculum 2026–2028
This page is under construction and the content is subject to change before publication in the spring of 2026.
This curriculum comes into effect on 1 August 2026.
About the programme
Master's Programme in Computer, Communication and Information Sciences (CCIS) is jointly organized by the School of Electrical Engineering and the School of Science. The CCIS programme’s core courses provide a strong foundation in computer science, communication engineering, and information science. In addition, students can immerse themselves in one of the specialization tracks or focused majors.
In CCIS, education is based both on scientific research and industrial state of the art. Students gain in-depth knowledge in one major. They learn how to apply scientific knowledge and scientific methods independently. Students acquire professional language and communication skills. All students are encouraged to include international, multidisciplinary, and entrepreneurial components as part of their studies.
Master of Science (Technology) degree is 120 ECTS credits. The degree consists of major studies, Master's thesis and elective studies. Some majors offer both long and compact options. Students taking a compact major take also a minor (20–25 credits). Students taking a long major may include an optional minor in their elective studies.
CCIS programme offers nine (9) majors. Some majors have also several study tracks.
The majors and study tracks are the following:
- Acoustics and Audio Technology
- Communications Engineering
- Computer Science
- Algorithms and Theory
- Big Data and Large-Scale Computing
- Secure Systems
- Quantum-Aware Software Systems
- Web Technologies, Applications, and Science
- Game Design and Development
- Human-Computer Interaction
- Human-Centred Design
- Intelligent and Interactive Systems
- XR and Blended Interaction
- Societal Computing
- Machine Learning, Data Science and Artificial Intelligence
- Signal Processing and Data Science
- Software Engineering
- Speech and Language Technology
Courses within the CCIS programme are mainly offered in English. However, you can choose to complete some of the courses included in Communications Engineering major and Computer Science - Web Technologies, Applications, and Science study track in Finnish/Swedish languages.
In addition, you can include a minor and/or elective studies offered in Finnish/Swedish in your degree.
The master’s thesis can be written in English, Finnish or Swedish. The language of the master’s thesis determines the language of the degree.
The languages used in teaching and studying
The language of instruction is the language in which the teaching is provided. The supplementary language of instruction is a language used alongside the language of instruction. The teaching offered in the supplementary language of instruction depends on the course: for a detailed description of the languages used in a given course, see the course’s MyCourses page.
You can complete study attainments, such as examinations or course assignments, using either the language of instruction or the supplementary language of instruction. In some courses, the language of study attainments may also be a language that is not used in teaching. The languages of study attainments offered are specified in Sisu under each study unit implementation.
* Compact major / long major. Some majors have only compact or long major. Check your major for more information.
** Only for compact major
Acoustics and Audio Technology (AAT)
The major in Acoustics and Audio Technology gives fundamental knowledge about acoustical phenomena, human hearing and audio technologies, and also facilitates the students to apply the knowledge in practice.
The fields of electroacoustics, room and building acoustics, noise, musical acoustics, spatial sound and audio signal processing are focused on the studies. A central field in the studies is technical psychoacoustics studying human hearing mechanisms, which is a cornerstone in the development of acoustical and audio technologies for human listeners. All these areas together constitute the field of communication acoustics, where there always exists a human listener at the end of the acoustic communication channel. Digital signal processing is currently a crucial tool in acoustics and audio engineering, and the teaching also emphasizes the understanding of its general principles and fundamental audio processing algorithms.
The target of the major is that the students could use their learning outcome flexibly in different tasks in industry and in academia. For example, the student should know why and how modern lossy audio codecs (mp3, AAC) work, or he/she should be able to measure, understand the perceptual aspects, and design the acoustics of a class room or a noise barrier. Some exemplar fields where the students are foreseen to be competent are psychoacoustics, spatial sound recording and reproduction, audio coding, music technology, acoustic measurements, active noise cancellation, audio signal processing, room and building acoustics, and environmental noise. If the student wants to work as a certified acoustics consultant in Finland, at least 10 cr on building technology courses is required.
The research conducted in Aalto University in the fields of this major has focused on following topics: spatial sound reproduction, concert hall acoustics, synthesis of musical instruments and natural sounds, loudspeaker and headphone reproduction, spatial sound psychoacoustics, digital filtering of audio signals, and modeling of room acoustics. The Aalto Acoustics lab is facilitated with world-class acoustical laboratories: three anechoic chambers, a standardized multichannel listening room, a variable acoustics room, sound-proof listening booths, workshops and tools to reproduce immersive audiovisual environments.
Upon completion of the AAT Major, the student will be able to:
- understand acoustic phenomena from the viewpoints of physics, signal processing, and human auditory perception.
- understand the theoretical foundations of acoustics and audio signal processing to be able to follow research in the field.
- design, implement, and evaluate the performance of an audio signal processing method for solving specific problems.
- design, implement, and analyze a psychoacoustic experiment to connect the auditory perception to recorded or synthetic audio signals.
- possess technical and professional skills to act as an acoustic consultant or as an acoustics/audio expert in R&D departments of high-tech companies.
Code: ELEC3030
Scope: Long (60 credits) or compact (40 credits) major
Professor in charge: Tapio Lokki (ELEC)
Professors: Johannes Arend (ELEC), Ville Pulkki (ELEC), Lauri Savioja (SCI), Vesa Välimäki (ELEC)
Abbreviation: AAT
Language of the major: English
Name of the major in Finnish: Akustiikka ja audioteknologia
Name of the major in Swedish: : Akustik och ljudteknik
School: Electrical Engineering (coordinator) and Science
The major can be completed either as a long (60 ECTS) major or a compact (40 ECTS) major. Students taking the compact major are required to also take an advanced studies level minor (20-25 ECTS). Students taking the long major may include an optional minor in their elective studies.
The major consists of 40 ECTS of compulsory courses and 20 ECTS of optional courses depending on the choice between long and compact major.
All the major courses, except the Acoustics Research Project and Master’s Thesis Process, are intended to be studied during the first year of master’s studies. The course ELEC-E5600 Communication Acoustics is a recommended prerequisite to the other major courses.
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
| ELEC-E5670 | Acoustical Measurements D | 5 | I English / 1st year |
| ELEC-E5600 | Communication Acoustics | 5 | I English / 1st year |
| ELEC-E0110 | Academic Skills in Master’s Studies | 3 | I-III English / 1st year |
| ELEC-E5610 | Acoustics and the Physics of Sound | 5 | II English / 1st year |
| ELEC-E5641 | Room and Building Acoustics D | 5 | II English / 1st year |
| ELEC-E5620 | Audio Signal Processing D | 5 | III-IV English / 1st year |
| ELEC-E5680 | Virtual Acoustics D | 5 | III-IV English / 1st year |
| ELEC-E0210 | Master’s Thesis Process | 2 | I-II, III-V English / 2nd year |
| ELEC-E5633 | Acoustics Research Project D | 5 | I-II English / 2nd year |
Choose 20 credits (long major) |
|||
| CIV-E1020 | Mechanics of Beam and Frame Structures | 5 | II English |
| CIV-E1050 | Heat and Mass Transfer in Buildings | 5 | I English |
| CIV-E3010 | Applied Building Physics and Design D | 5 | V English |
| CIV-E3020 | Design of Energy Efficient Buildings D | 5 | II English |
| CIV-E3030 | Indoor Air Quality D | 5 | IV English |
| CS-C3100 | Computer Graphics | 5 | I-II English |
| CS-C3120 | Human-Computer Interaction | 5 | I-II English |
| CS-E4715 | Supervised Machine Learning D | 5 | I-II English |
| CS‐E4200 | Emergent User Interfaces D | 5 | III-V English |
| CS‐E4850 | Computer Vision D | 5 | I-II English |
| CS‐E5520 | Advanced Computer Graphics D | 5 | 2026-2027: No teaching 2027-2028: III-IV English |
| CS-E5690 | Audio Programming Project D | 3-5 | V English |
| ELEC-E5410 | Signal Processing for Communications | 5 | I-II English |
| ELEC-E5424 | Convex Optimization D | 5 | I-II English |
| ELEC-E5431 | Large Scale Data Analysis D | 5 | III-IV English |
| ELEC-E5440 | Statistical Signal Processing D | 5 | I-II English |
| ELEC-E5481 | Machine Learning for Signal Processing | 5 | I-II English |
| ELEC-E5500 | Speech Processing | 5 | I English |
| ELEC-E5510 | Speech Recognition D | 5 | II English |
| ELEC-E5550 | Statistical Natural Language Processing D | 5 | III-IV English |
| ELEC-E5523 | Speech Synthesis D | 5 | IV-V English |
| ELEC-E5650 | Electroacoustics D | 5 | IV-V English |
| ELEC-E5660 | Special Assignment in Acoustics and Audio Technology D | 1-10 | I-summer English |
| NBE-E4310 | Biomedical Ultrasonics D | 5 | I-II English |
| CS-E4890 | Deep Learning D | 5 | III-IV English |
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Some majors have restrictions on the selection of a minor. Please check those from section Major 60 / 40 ECTS. The minor is confirmed in the Personal Study Plan (HOPS).
Students taking a long major can include a minor in elective studies.
More information on Aalto University’s minor subjects is in in Aalto Minors.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national
language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages. - If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies
Communications Engineering (CE)
The major in Communications Engineering gives a solid understanding of modern communications and networking technology. The program builds on a scientific foundation of concepts, tools and solution approaches, covering both theoretical and practical aspects of Communications Engineering. Students specialize in either networked systems, wireless communication or ubiquitous computing. The main learning objective of the program is that graduates of the major are prepared to take on the challenges of expert work in this rapidly developing field. For this, the students reach the state-of-the art of technology in at least one of the expertise areas of the major. This opens up a possibility for a successful career in industry, research organizations or in postgraduate studies. During the studies the students learn to communicate efficiently and fluently using the professional language of the field. Students are encouraged to include international, multidisciplinary, and entrepreneurial components as part of their studies.
Code: ELEC3029
Scope: Long major (60 credits)
Professor in charge: Olav Tirkkonen
Professors: Riku Jäntti, Stephan Sigg, Jukka Manner, Patric Östergård, Risto Wichman, Antti Oulasvirta, Yu Xiao, Gopika Premsankar, Petri Mähönen
Languages of the major: English, Finnish, Swedish
Abbreviation: CE
Name of the major in Finnish: Tietoliikennetekniikka
Name of the major in Swedish: Datakommunikationsteknik
School: Electrical Engineering
The major consists of compulsory part and optional part. The optional part offers three different expertise areas: Networked Systems, Wireless Communications and Ubiquitous Computing.
The table shows the language of instruction and possible supplementary language of instruction in parenthesis.
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
| ELEC-E0110 | Academic skills in master's studies | 3 | I-III EN (FI) / 1st year |
| ELEC-E0210 | Master’s Thesis Process | 2 | I-V EN (FI) / 2nd year |
| ELEC-E7120 | Wireless Systems | 5 | I English / 1st year |
| ELEC-E7140 | Networked Systems | 5 | I English / 1st year |
| ELEC-E7263 | Ambient Intelligence – Communications and Sensing | 5 | I-II English / 1st year |
| ELEC-E7825 | Communications Ecosystems and Techno-Economics | 5 | II English / 1st year |
| ELEC-E7911 | Special Project in Communications Engineering | 5 | III-V EN (FI) / 1st year |
Choose 30 ECTSCourses are grouped under three expertise areas: Networked Systems, Wireless Communications, and Ubiquitous Computing. It is recommended to select 20 - 30 ECTS from one of the expertise areas. |
|||
| Networked Systems | |||
| ELEC-E7470 | Cybersecurity D2,3 | 5 | V English / 1st year |
| ELEC-E7132 | Internet Traffic Measurements and Analysis | 5 | III - IV EN (FI) / 1st year |
| ELEC-E7321 | Advanced Networking D | 5 | III - IV EN (FI) / 1st year |
| ELEC-E7331 | Laboratory Course in Networking and Cloud Technologies | 5 | I – II EN (FI) / 2nd year |
| ELEC-E7316 | Distributed Applications D | 5 | III – IV English / 1st year |
| ELEC-E7451 | Network Performance Analysis | 5 | IV-V EN (FI) / 1st year |
| Wireless Communications | |||
| ELEC-E5410 | Signal Processing for Communications | 5 | I - II EN (FI) / 2nd year |
| ELEC-E7211 | Digital Wireless Communication D | 5 | I-II EN (FI) / 2nd year |
| ELEC-E7230 | Mobile Communication Systems1 | 5 | II English / 1 or 2nd year |
| ELEC-E7240 | Coding Methods D | 5 | III EN (FI) / 1st year |
| ELEC-E7250 | Laboratory Course in Communications Engineering | 5 | III - V EN (FI) / 1st year |
| ELEC-E7340 | Machine Learning for Wireless Communications D | 5 | III – IV English / 1st year |
| ELEC-E5440 | Statistical Signal Processing D | 5 | I-II English / 1st or 2nd year |
| Ubiquitous Computing | |||
| ELEC-C7222 | Embedded Programming with Communication Devices2 | 5 | III – V English / 1st year |
| ELEC-E7840 | Smart Wearables | 3-6 | III – IV English / 1st year |
| ELEC-E7845 | Smart Wearables II D | 6 | I – II English / 2nd year |
| ELEC-E7770 | Computational Cognitive Modeling D | 5 | III – IV English / 1st year |
| ELEC-E5431 | Large Scale Data Analysis D1,2 | 5 | III-IV English / 1st year |
| ELEC-E7852 | Computational Design and Interaction D | 5 | II English / 1st or 2nd year |
1 Also suitable for Networked Systems -expertise area
2 Also suitable for Wireless Communications -expertise area
3 Also suitable for Ubiquitous Computing -expertise area
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Some majors have restrictions on the selection of a minor. Please check those from section Major 60 / 40 ECTS. The minor is confirmed in the Personal Study Plan (HOPS).
Students taking a long major can include a minor in elective studies.
More information on Aalto University’s minor subjects is in in Aalto Minors.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national
language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages. - If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies
Computer Science
Computer Science is the study of computing and software systems that are nowadays deeply embedded in our daily life across different fields: industry, commerce, healthcare, media, and art to name a few. The major in Computer Science is grounded in leading-edge computing research at Aalto University and offers a deep understanding on the design and analysis of advanced software and computing technologies. Graduates from the major master the theory and practice of advanced computing across a broad spectrum of systems, from Internet-scale distributed platforms to emerging quantum computing infrastructure.
Code: SCI3042
Extent: Long (60 credits) or compact (40 credits) major. Students taking a compact major take also a minor (20–25 credits). Students taking a long major may include an optional minor in their elective studies.
Responsible professor: Petri Vuorimaa
Abbreviation: CS
School: School of Science
Name of the major in Finnish: Tietotekniikka
Name of the major in Swedish: Datateknik
Available study tracks:
- Algorithms and Theory
- Big Data and Large-Scale Computing
- Secure Systems
- Quantum-Aware Software Systems
- Web Technologies, Applications, and Science
The major consists of core courses, track courses, and optional computer-science courses. The purpose of the core courses is to ensure that all students in the major have a solid basic knowledge of computer science and software technology topics. The track courses provide deeper understanding of a specific topic and sufficient background knowledge for the Master's thesis in the track's area. After the core and track courses, most students will be left with quite a few credits for other computer-science courses.
Students must complete at least five (5) Computer Science major core courses, including the compulsory core course(s) defined by each track and presented in the course table. The core courses can also be completed in the Bachelor's degree, which reduces the number of required core courses. Students who have completed equivalent courses at another university can be excused from taking the core courses with agreement of the professor in charge of the study track.
In addition to the major core courses, the students have to take the track course(s).
Responsible professor: Jara Uitto
Extent: Long (60 ECTS) or compact (40 ECTS) major as CS track. as CS track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Abbreviation: ALT
Objectives
The Algorithms and Theory study track equips students with a strong methodological and mathematical foundation to understand and improve the algorithms that drive science, technology, and society. The track covers the modelling, design, and analysis of advanced algorithms and computing systems from massively distributed infrastructure to quantum computing. In addition to skills in advanced programming and automated reasoning, students gain an understanding of the foundations of cryptography and computational complexity theory and learn to examine societal problems from a computational perspective. Studies in the track form an excellent basis for pursuing a doctoral degree, and competitively selected students can start working toward their doctoral degree already during their master’s studies.
Learning Outcomes
- Students can design, analyse, and implement novel, efficient algorithms for a wide range of computational problems and models of computing.
- Students can formalise computational problems, classify them according to their computational complexity, and use such classifications as a guidance in choosing the right methodology for tackling hard problems.
- Students can build modern cryptographic primitives based on computational hardness assumptions.
- Students master fundamental techniques in computational logic and are able to solve computational problems using state-of-the-art algorithms and tools for automated reasoning.
- Students can model and specify complex systems in a rigorous way, use computational techniques to verify and synthesise such systems, and examine societal problems through a computational lens.
Content and Structure
The major consists of core courses, track courses, and optional computer-science courses. The purpose of the core courses is to ensure that all students in the major have a solid basic knowledge of computer science and software technology topics. The track courses provide deeper understanding of a specific topic and sufficient background knowledge for the Master's thesis in the track's area. After the core and track courses, most students will be left with quite a few credits for other computer-science courses.
Students must complete at least five (5) Computer Science major core courses, including the compulsory core course(s) defined by each track and presented in the course table. The core courses can also be completed in the Bachelor's degree, which reduces the number of required core courses. Students who have completed equivalent courses at another university can be excused from taking the core courses with agreement of the professor in charge of the study track.
In addition to the major core courses, the students have to take the track course(s).
The track optional courses listed below are recommended but not required. The rest of the credits for the major can consist of any Master-level computer science courses.
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
Compulsory CS core courses, 15 ECTSFor Algorithms and Theory (ALT) study track |
|||
| CS-E3190 | Principles of Algorithmic Techniques | 5 | I-II/1st year |
| CS-E3220 | Declarative Programming | 5 | I-II/1st year |
| CS-E4700 | Logic and Hard Computational Problems | 5 | I-II/1st year |
Choose at least 10 ECTSComputer Science core courses |
|||
| CS-C3170 | Web Software Development | 5 | I-II, III-V, summer/1st year |
| CS-C3130 | Information Security | 5 | I/1st year |
| CS-E4190 | Cloud Software and Systems | 5 | I-II/1st year |
| CS-E4715 | Supervised Machine Learning | 5 | I-II/1st year |
| ELEC-E7852 | Computational Design and Interaction | 5 | II/1st year |
| CS-C3100 | Computer Graphics | 5 | I-II/1st year |
| CS-E4780 | Scalable Systems and Data Management | 5 | I-II/1st year |
Choose at least 15 ECTSAlgorithms and Theory (ALT): Track courses |
|||
| CS-E4340 | Cryptography | 5 | I-II |
| CS-E4370 | Applied Cryptography | 5 | III-IV |
| CS-E4500 | Advanced Course in Algorithms | 5 | III-IV |
| CS-E4510 | Distributed Algorithms | 5 | I-II |
| CS-E4530 | Computational Complexity Theory | 5 | III-IV |
| CS-E4800 | Artificial Intelligence | 5 | III-IV |
| CS-E4720 | Computational Geometry | 5 | III–IV |
| CS-C3260 | Practical Quantum Computing | 5 | I-II |
| CS-E5485 | Algorithms and Society | 5 | 2026-2027: no teaching, 2027-2028: I |
Long major: optional coursesTo complete a long major (60 ECTS), choose optional courses in addition to the compact major (40 ECTS). Other optional courses can also be included per agreement with a professor in charge of the track. The track optional courses listed below are recommended but not required. The rest of the credits for the major can consist of any Master-level computer science courses. |
|||
| CS-E4380 | Special Course: Advanced Cryptography | 5 | I-II (even years) |
| MS-E1688 | Special Course: Advanced Cryptography | 5 | I-II (odd years) |
| CS-E4565 | Combinatorics of Computation | 5 | V |
| CS-E4580 | Programming Parallel Computers | 5 | V |
| CS-E4690 | Programming Parallel Supercomputers | 5 | I-II |
| CS-E4595 | Competitive Programming | 5 | I-II |
| CS-E4641 | Principles and Techniques of Data Platforms | 5 | III-IV |
| MS-C1081 | Abstract Algebra | 5 | III |
| MS-C1342 | Linear Algebra | 5 | II (FI), V (EN) |
| MS-E1050 | Graph Theory | 5 | I (no teaching 2027-2028) |
| MS-E1053 | Combinatorics | 5 | I (no teaching 2026-2027) |
| MS-E1110 | Number Theory | 5 | II |
| MS-E1111 | Galois Theory | 5 | IV |
| MS-E1052 | Combinatorial Network Analysis | 5 | II (no teaching 2026-2027) |
| MS-E1142 | Computational Algebraic Geometry | 5 | V (no teaching 2026-2027) |
| MS-E1150 | Matrix Theory | 5 | II (no teaching 2027-2028) |
| MS-E1600 | Probability Theory | 5 | I |
| MS-E1624 | High-Dimensional Statistics | 5 | IV |
| MS-E1651 | Numerical Matrix Computations | 5 | I |
| MS-E2121 | Linear Optimization | 5 | III-IV |
| MS-E2122 | Nonlinear Optimization | 5 | I-II |
| MS-E2145 | Combinatorial Optimization | 5 | III-IV |
| CS-E4003 | Special Assignment in Computer Science | 1-10 | Agreed with a teacher |
| CS-E4006 | Research Experience Project in Computer Science | 5 | Agreed with a teacher |
Responsible professor: Bo Zhao
Extent: Long (60 ECTS) or compact (40 ECTS) major as CS track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Objectives
The track on big data and large-scale computing provides the students with a strong background to cope with the challenges arising from the growth of data and information in our society. The track covers a wide range of topics in data management, data processing, algorithmics, data science, and data analysis. The teaching and instruction of the students is conducted by the leading experts in the focus areas of this track.
Learning Outcomes
The track aims to educate professionals who are capable of dealing with the different aspects of big data and large-scale computing. The graduates of the track will be able to cope with the main big data challenges:
- collecting and storing data,
- dealing with data complexity and heterogeneity,
- developing efficient algorithms to process large datasets,
- utilizing scalable frameworks for different types of batch and streaming data processing,
- building data-intensive scalable systems in cloud platforms,
- employing distributed and parallel computing for data processing and data services,
- discovering patterns and hidden structure in the complex and large datasets,
- building models and making inferences from data-in-motion and data-at-rest,
- learning to visualize large datasets and
- designing data governance policies and techniques for large-scale data systems.
Content and Structure
The major consists of core courses, track courses, and optional computer-science courses. The purpose of the core courses is to ensure that all students in the major have a solid basic knowledge of computer science and software technology topics. The track courses provide deeper understanding of a specific topic and sufficient background knowledge for the Master's thesis in the track's area. After the core and track courses, most students will be left with quite a few credits for other computer-science courses.
Students must complete at least five (5) Computer Science major core courses, including the compulsory core course(s) defined by each track and presented in the course table. The core courses can also be completed in the Bachelor's degree, which reduces the number of required core courses. Students who have completed equivalent courses at another university can be excused from taking the core courses with agreement of the professor in charge of the study track.
In addition to the major core courses, the students have to take the track course(s). The track optional courses listed below are recommended but not required. Note that course substitution/replace will be considered case by case but courses for bachelor level (course code starts with CS-C****) will be likely rejected. Students should be carefully checked this condition.
If needed, students should consider taking additional courses to have sufficient background required to study courses listed for this track. For example, when missing background about operating systems, computer networks, computer architectures and programming languages, students can apply suitable courses as optional/elective ones.
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
Compulsory CS core courses, 10 ECTSFor Big Data and Large-Scale Computing track |
|||
| CS-E4190 | Cloud Software and Systems | 5 | I-II/1st year |
| CS-E4780 | Scalable Systems and Data Management | 5 | I-II/1st year |
Choose at least 15 ECTSComputer Science core courses |
|||
| CS-E4715 | Supervised Machine Learning | 5 | I-II/1st year |
| CS-E3220 | Declarative Programming | 5 | I-II/1st year |
| CS-C3170 | Web Software Development | 5 | I-II, III-V, summer/1st year |
| CS-C3130 | Information Security | 5 | I/1st year |
| CS-E3190 | Principles of Algorithmic Technique | 5 | I-II/1st year |
| ELEC-E7852 | Computational Design and Interaction | 5 | II/1st year |
| CS-C3100 | Computer Graphics | 5 | I-II/1st year |
| CS-E4700 | Logic and Hard Computational Problems | 5 | I-II |
Choose at least 15 ECTSBig Data and Large-Scale Computing track courses |
|||
| CS-E4650 | Methods of Data Mining | 5 | I-II |
| CS-E4641 | Principles and Techniques of Data Platforms | 5 | III-IV |
| CS-E4690 | Programming Parallel Supercomputers | 5 | I-II |
| CS-E4580 | Programming Parallel Computers | 5 | V |
| CS-E4645 | Research Project on Data Intensive Computing | 5 | III-V |
Long major: optional coursesTo complete a long major (60 ECTS), choose optional courses in addition to the compact major (40 ECTS). Other optional courses can also be included per agreement with a professor in charge of the track. The track optional courses listed below are recommended but not required. Note that course substitution/replace will be considered case by case but courses for bachelor level (course code starts with CS-C****) will be likely rejected. Students must carefully check this condition. |
|||
| CS-E4890 | Deep Learning | 5 | III-IV |
| CS-E4500 | Advanced Course in Algorithms | 5 | III-IV |
| CS-E4660 | Advanced Topics in Software Systems | 5 | I-II |
| CS-E4840 | Information Visualization | 5 | IV |
| CS-E4950 | Software Architectures | 5 | III-V |
| CS-E4770 | Designing and Building Scalable Web Applications | 5 | I-II, III-V |
Responsible professor: Lachlan Gunn
Extent: Long (60 credits) or compact (40 credits) major as CS track. Students taking a compact major also take a minor (20-25 credits). Students taking the long major may include an optional minor in their elective studies.
Abbreviation: Security
Objectives
The Secure Systems track gives students both practical skills and theoretical insights into secure systems engineering. The courses cover a broad range of principles, methods, and technologies for information security and cryptography. Students are encouraged to combine theoretical knowledge and security expertise with product development skills. The graduates are well prepared for international industrial R&D jobs, security engineering and consulting, various expert roles, and doctoral studies at Aalto University and internationally.
Learning outcomes
The learning outcomes of the track are the following:
- Students understand the fundamental concepts and adversarial setting of information security. They have practical skills for designing, analyzing, and evaluating secure computing systems. They are familiar with various security solutions and technologies and how they fail.
- Students understand the central concepts, methods, and mathematical foundations of cryptography and can apply this knowledge to engineering tasks.
- Students have in-depth knowledge of their chosen thesis topic and can apply it to solving technical and scientific problems in creative ways.
Students have strong software development skills and other technical and professional skills that enable them to drive the development of secure products and services in an industrial R&D environment, and they are qualified to continue to doctoral studies.
Content and structure
The track starts with introductory courses in information security and cryptography, which lead the student to the fundamental concepts and ways of thinking. Students can then take advanced courses in network security, platform security, secure systems engineering, and security management. For example, they will learn threat modeling, security analysis, and a critical approach to analyzing and selecting security solutions. They can learn more about cryptography, including its applications and mathematical foundations. All these topics are closely linked to research at Aalto University. Beyond security topics, students are encouraged to learn software engineering and data science skills and technologies for distributed and cloud computing. The studies can include selected security and cryptography courses from other Finnish universities. Students should discuss their individual learning and career goals with the teachers.
The courses combine theoretical studies with hands-on exercises and projects where the new knowledge is applied. Much of the student’s time is spent on group and individual assignments that train problem-solving, secure system design, and engineering skills. In a seminar course, the students can learn to write a technical or research article and present their work. The studies include opportunities for networking with local and European companies, and our industry partners contribute to the teaching and host interns and master’s thesis projects.
Students must complete at least five (5) Computer Science major core courses, including the compulsory core course(s) defined by each track and presented in the course table. The core courses can also be completed in the Bachelor's degree, which reduces the number of required core courses. Students who have completed equivalent courses at another university can be excused from taking the core courses with agreement of the professor in charge of the study track.
In addition to the major core courses, the students have to take the track course(s).
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
Compulsory CS core course, 5 ECTSFor Secure Systems track |
|||
| CS-C3130 | Information Security | 5 | I/1st year |
Choose at least 20 ECTSComputer Science core courses |
|||
| CS-E4190 | Cloud Software and Systems | 5 | I-II/1st year |
| CS-C3170 | Web Software Development | 5 | I-II, III-V, summer/1st year |
| CS-E3190 | Principles of Algorithmic Techniques | 5 | I-II/1st year |
| CS-E3220 | Declarative Programming | 5 | I-II/1st year |
| CS-E4715 | Supervised Machine Learning | 5 | I-II/1st year |
| ELEC-E7852 | Computational Design and Interaction | 5 | II/1st year |
| CS-C3100 | Computer Graphics | 5 | I-II/1st year |
| CS-E4700 | Logic and Hard Computational Problems | 5 | I-II |
| CS-E4780 | Scalable Systems and Data Management | 5 | I-II/1st year |
Choose at least 15 ECTSSecure Systems: Track courses |
|||
| CS-E4300 | Network Security | 5 | II/1st or 2nd year |
| CS-E4340 | Cryptography | 5 | I-II/1st year |
| CS-E4350 | Security Engineering | 5 | III-IV/1st year |
| CS-E4760 | Platform Security | 5 | III-IV/1st year |
| CS-E4370 | Applied Cryptography | 5 | III-IV/1st year |
| MS-E1688 | Special Course: Advanced Cryptography | 5 | 2026-2027: no teaching 2027-2028: I-II |
Long major: optional coursesTo complete a long major (60 ECTS), the student selects elective courses on top of the compact major (40 ECTS). Any master-level computer science, communications, and mathematics course may be included with the prior agreement of the professor in charge of the track. Advanced security and cryptography courses from other universities (FiTech and RIPA platforms) can also be included with a prior written agreement. The track optional courses listed below are recommended but not required. |
|||
| CS-E4330 | Special Course in Information Security * | 5 | varies |
| MS-C1081 | Abstract Algebra | 5 | III/1st year |
| MS-E1110 | Number Theory | 5 | II/1st year |
| MS-E1111 | Galois theory | 5 | IV/1st year |
| MS-E1600 | Probability Theory | 5 | I/1st year |
* Course code varies and has additional number in the end (CS-E4330xx). Check these in Sisu.
Responsible professor: Alexandru Paler
Extent: Long (60 credits) or compact (40 credits) major as CS track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Abbreviation: QSS
Objectives
The Quantum-Aware Software Systems (QSS) track equips students with the advanced theoretical and practical skills necessary to develop, optimize, and manage the classical and quantum software that interfaces with, leverages, or is inspired by quantum computing principles.
The students graduating from the track will have a strong technical background on many of the modern core technologies for classical and quantum computing stacks. For example, they will be professionals capable of designing, architecting, and implementing hybrid classical-quantum applications, focusing on near-term quantum devices and future fault-tolerant quantum computers. At the same time, they will be experts in software engineering methodologies of quantum computing, including testing quantum programs, and managing the quantum computing stack.
Students will have job opportunities in both the classical computing industry and the fast growing quantum technology industries. Moreover, students interested in pursuing doctoral studies after their M.Sc. degree can easily transfer to doctoral schools.
Learning outcomes
- Students can describe the mathematical foundations of quantum computation and differentiate between various quantum computing architectures, such as monolithic, distributed and heterogeneous.
- Students can analyze the structure and requirements of classical operating systems, containerization technologies, and middleware necessary for efficiently scheduling and executing classical, quantum and hybrid workloads.
- Students can develop and debug high-performance classical software components that effectively manage and interact with classical, quantum and hybrid workloads.
- Students can conduct independent research, formulate novel quantum-aware solutions for real-world problems, and effectively communicate technical findings to both specialist and non-specialist audiences.
Content and structure
The major consists of core courses, track courses, and optional computer science courses. The purpose of the core courses is to ensure that all students in the major have a solid basic knowledge of computer science and software technology topics. The track courses provide deeper understanding of a specific topic and sufficient background knowledge for the master's thesis in the track's area. The core expertise is built upon a mandatory compact major, which includes courses that span the full quantum-classical computational stack, and a seminar focusing on quantum software. To complete the long major, students select additional advanced courses which can focus on classical computing, quantum computing, HPC or AI.
Students must complete at least five (5) Computer Science major core courses, including the compulsory core course(s) defined by each track and presented in the course table. The core courses can also be completed in the Bachelor's degree, which reduces the number of required core courses. Students who have completed equivalent courses at another university can be excused from taking the core courses with agreement of the professor in charge of the study track.
In addition to the major core courses, the students have to take the track course(s).
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
Compulsory CS core course, 5 ECTSFor Quantum-Aware Software Systems (QSS) study track |
|||
| CS-E3220 | Declarative Programming | 5 | I-II/1st year |
Choose at least 20 ECTSComputer science core courses |
|||
| CS-C3130 | Information Security | 5 | I/1st year |
| CS-E3190 | Principles of Algorithmic Techniques | 5 | I-II/1st year |
| CS-E4715 | Supervised Machine Learning | 5 | I-II/1st year |
| ELEC-E7852 | Computational Design and Interaction | 5 | II/1st year |
| CS-C3100 | Computer Graphics | 5 | I-II/1st year |
| CS-E4700 | Logic and Hard Computational Problems | 5 | I-II |
| CS-C3170 | Web Software Development | 5 | I-II, III-V, summer/1st year |
| CS-E4190 | Cloud Software and Systems | 5 | I-II/1st year |
| CS-E4780 | Scalable Systems and Data Management | I-II/1st year | |
Choose at least 15 ECTSQuantum-Aware Software Systems (QSS) study track courses |
|||
| CS-C3141 | Operating Systems: From Classical to Quantum | 5 | I-II/1st year |
| CS-E4800 | Artificial Intelligence | 5 | III-IV/1st year |
| CS-E4690 | Programming Parallel Supercomputers | 5 | I-II/2nd year |
| CS-E4013 | Seminar in Computer Science - Quantum Software | 5 | III-V/1st year |
Long major: optional coursesTo complete a long major (60 ECTS), the student selects elective courses on top of the compact major (40 ECTS). The track optional courses listed below are recommended but not required. The rest of the credits for the major can consist of any Master-level computer science courses. |
|||
| CS-C3260 | Practical Quantum Computing | 5 | I-II/2nd year |
| ELEC-C9440 | Quantum Information | 5 | V/1st year |
| PHYS-C0254 | Quantum Circuits | 5 | IV |
| ELEC-E8125 | Reinforcement Learning | 5 | I-II / 2nd year |
| CS-E4890 | Deep Learning | 5 | III-IV / 1st year |
| CS-E4500 | Advanced Course in Algorithms | 5 | III-IV |
| CS-E5740 | Complex Networks | 5 | I-II |
| ELEC-C7420 | Basic Principles in Networking* | 5 | III-IV/1st year |
| CS-E4641 | Principles and Techniques of Data Platforms | 5 | III-IV/first year or 2nd year |
| CS-E4300 | Network Security | 5 | II |
| CS-E4770 | Designing and Building Scalable Web Applications | 5 | III-V |
| ELEC-C7440 | Computer Architectures with RISC-V | 5 | III-IV/2nd year |
| CS-E4580 | Programming Parallel Computers | 5 | V/1st year |
| CS-E4003 | Special Assignment in Computer Science | 1-10 | Agreed with a teacher |
| CS-E4006 | Research Experience Project in Computer Science | 5 | Agreed with a teacher |
*NOTE! This course (or an equivalent course in computer networks) is a pre-requisite of CS-E4190 Cloud Software and Systems.
Responsible professor: Petri Vuorimaa
Extent: Long (60 credits) or compact (40 credits) major as CS track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Abbreviation: WEB
Objectives
Web may be the most important invention in the field of data processing since the invention of the computer itself, when the influence on society and business life is considered. The teaching in the Web Technologies, Applications, and Science track handles subject areas of web services and web content in a versatile way. The students learn to develop content to the web and control the technologies related to presenting and transferring that data.
One relevant learning goal is the ability to develop web services to the users. In the deeper level this entails intelligent services and applications. Other core content is related to developing web services to machines. On the higher levels than XML, the WWW is based on the semantic web technologies, where the core issues are presenting the knowledge, logics and inference. Human labor, structural data or different methods of automatic annotation (structural or statistical methods) are used to create these kinds of structures.
Content and structure
The major consists of core courses, track compulsory courses, and optional computer-science courses. The purpose of the core courses is to ensure that all students in the major have a solid basic knowledge of computer science and software technology topics. The track courses provide deeper understanding of a specific topic and sufficient background knowledge for the Master's thesis in the track's area. After the core and track compulsory courses, most students will be left with quite a few credits for other computer-science courses.
Students must complete at least five (5) Computer Science major core courses, including the compulsory core course(s) defined by each track and presented in the course table. The core courses can also be completed in the Bachelor's degree, which reduces the number of required core courses. Students who have completed equivalent courses at another university can be excused from taking the core courses with agreement of the professor in charge of the study track.
In addition to the major core courses, the students have to take the track compulsory course(s).
In the Teaching column of the table, the language of instruction for the course is indicated. Supplementary language of instruction is provided in parentheses. For example: EN or EN(FI). (EN=English, FI=Finnish)
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
Compulsory CS core course, 5 ECTSFor Web Technologies, Application and Science (WEB) study track |
|||
| CS-C3170 | Web Software Development * | 5 | I-II, III-V, summer/1st year, EN |
Choose at least 20 ECTSComputer science core courses |
|||
| CS-E4190 | Cloud Software and Systems | 5 | I-II/1st year. EN |
| CS-C3130 | Information Security | 5 | I/1st year, EN |
| CS-E3190 | Principles of Algorithmic Techniques | 5 | I-II/1st year, EN |
| CS-E3220 | Declarative Programming | 5 | I-II/1st year, EN |
| CS-E4715 | Supervised Machine Learning | 5 | I-II/1st year, EN |
| ELEC-E7852 | Computational Design and Interaction | 5 | II/1st year, EN |
| CS-C3100 | Computer Graphics | 5 | I-II/1st year, EN |
| CS-E4700 | Logic and Hard Computational Problems | 5 | I-II/1st year EN, FI |
| CS-E4780 | Scalable Systems and Data Management | 5 | I-II/1st year, EN |
Choose all courses, 10 ECTSTrack compulsory courses. |
|||
| CS-E4400 | Design of WWW Services * | 5 | I-II/1st year, EN |
| CS-E4460 | WWW Applications | 5 | I-II/2nd year EN (FI) |
Choose 0-20 ECTSTo complete the major (compact major 40 ECTS, long major 60 ECTS), the student selects optional courses. The track optional courses listed below are recommended but not required. The rest of the credits for the major can consist of any Master-level computer science courses. |
|||
| CS-E4410 | Semantic Web | 5 | III-IV/1st year, EN |
| CS-E4770 | Designing and Building Scalable Web Applications | 5 | III-V, EN |
| CS-E4271 | Cross-Platform Development | 5 | I-II, EN |
| CS-E4265 | Multimedia Systems | 5 | I-II, EN |
| CS-E5220 | User Interface Construction | 5 | II/1st year, EN |
| CS-E4003 | Special Assignment in Computer Science * | 1-10 | Agreed with a teacher |
| CS-E4800 | Artificial Intelligence | 5 | III-IV/1st year, EN |
| CS-E5740 | Complex Networks | 5 | I-II, EN |
| CS-E4641 | Principles and Techniques of Data Platforms | 5 | III-IV, EN |
| CS-E4840 | Information Visualization | 5 | IV, EN |
| CS-E5010 | Research Methods Foundations ** | 3 | I, EN |
| CS-E5011 | Research Methods: Case Studies & Design Science ** | 2 | II, EN |
| CS-E5012 | AI-based Data Synthesis & Analysis ** | 2 | II, EN |
*Language of study attainment English, Finnish
**If choosing the research methods courses, it is recommended to choose CS-E5010 AND either CS-E5011 OR CS-E5012.
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Students taking a long major can include a minor in elective studies. The minor is confirmed in the Personal Study Plan (HOPS).
More information on Aalto University’s minor subjects is in Aalto Minors page.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages.
- If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies.
Game Design and Development
The objective of the major is to educate game programmer-designers* who understand both technology and the player’s point of view, and can thus 1) both implement and design games or at least participate in a game's design, and 2) if working as a game programmer, take responsibility of the myriad design decisions that are not necessarily communicated in a design document and only arise during implementation.
The students will learn about game design, development, production, and technology using a project-oriented, hands-on with minds-on approach. The project courses emphasize interdisciplinary and collaborative work. The teacher network includes both game industry professionals and game scholars.
* You may also substitute “engineer” or “computer scientist” for “programmer”.
Learning outcomes
- Deepening of technological expertise already built during Bachelor level studies (compulsory and optional technical courses on computer graphics, research methods, and machine learning)
- Building a wide set of cross-disciplinary design, production, and teamworking skills (compulsory Department of Art and Media courses, especially Game Project 1 & 2.
- Deeper understanding of each student's specific areas of interest (a large selection of optional courses).
Code: SCI3046
Extent: Long (60 credit) or compact (40 credits) major. Students taking a compact major take also a minor (20-25 cr). Students taking a long major may include an optional minor in their elective studies.
Responsible Professor: Perttu Hämäläinen
Abbreviation: Game
School: School of Science
Name of the major in Finnish: Pelisuunnittelu ja -tuotanto
Name of the major in Swedish: Speldesign och spelutveckling
The Game Design and Development CCIS M.Sc. major is organized in collaboration with Department of Art and Media of Aalto ARTS, which offers a M.A. “sibling major” with the same name. Game development is a multidisciplinary field, and the M.Sc. and M.A. majors share a large portion of the courses. The obligatory courses differ, however, and the CCIS students should expect to work in a more technical role, e.g., when creating a joint thesis game with ARTS students. Multidisciplinarity is also emphasized by the high flexibility of elective studies, where one can include, e.g., 3D animation, interactive storytelling and interaction design in addition to computer science.
Students take the Major compulsory courses. In addition, they take Major optional courses. Listing of optional courses is not exhaustive. Additionally, students may choose courses from all Aalto schools according to the personal study plan. It is strongly suggested that students venture outside their comfort zone and do not, for example, take a course in web software development if they already possess the equivalent skills and knowledge.
| Code | Course name | ECTS credits | Teaching |
|---|---|---|---|
Major compulsory courses (40 ECTS) |
|||
| AMX-E5012 | Science of Game Design | 3 | II/1st year |
| AMX-E5014 | Game Tools and Technology | 6 | III-IV/1st year |
| AXM-E5009 | Game Design | 3 | I/1st year |
| AXM-E5010 | Game Design Fundamentals | 3 | II, Summer/1st year |
| AXM-E5003 | Game Project I | 6 | I-II/1st year |
| AXM-E5013 | Game Project II | 6 | III-V/1st year |
| CS-C3100 | Computer Graphics * | 5 | I-II/1st year |
| CS-C3240 | Machine Learning * | 5 | I/1st or 2nd year |
| CS-E5010 | Research Methods Foundation | 3 | I/2nd year |
Long major: Choose 20 ECTSTo complete a long major (60 ECTS), the student selects optional courses on top of the compact major (40 ECTS). Recommended optional courses are listed below. It is also possible to include a personal study/research project; contact Prof. Perttu Hämäläinen to discuss possible project topics. |
|||
| Art and Design | |||
| AXM-E5008 | Games Now! | 3 | I-V |
| AXM-E5007 | Advanced Topics in Game Design | 3 | III |
| AXM-E5006 | Game Seminar | 3 | I-V |
| AXM-E5011 | Game Seminar 2 | 3 | I-V |
| AXM-E6008 | Game Audio Workshop | 3 | I-II |
| CS-C3120 | Human-Computer Interaction | 5 | I-II |
| AXM-E7003 | Interaction Design | 3 | II |
| AXM-E0003 | Art of Writing | 6 | IV-V |
| AXM-E7007 | Generative and Interactive Narratives | 6 | III-IV |
| AXM-E6001 | Introduction to Sound Design and Music | 6 | I |
| AXM-E0401 | Introduction to 3D Animation | 3 | summer |
| Virtual Reality and embodied interaction | |||
| AXM-E7008 | Embodied Interaction | 6 | III-IV |
| AXM-E0402 | Introduction to Virtual Reality | 3 | I |
| AXM-E0403 | Coding Virtual Worlds | 6 | I |
| AXM-E0404 | Designing and Creating Virtual Worlds | 6 | II |
| Technical courses | |||
| CS-E5012 | Research Methods: AI-based Data Synthesis & Analysis | 2 | II |
| CS-E5520 | Advanced Computer Graphics | 5 | III-IV |
| CS-E4715 | Supervised Machine Learning | 5 | I-II |
| CS-E4890 | Deep Learning | 5 | III-IV |
| CS-E4891 | Deep Generative Models | 5 | IV-V |
| ELEC-E7770 | Computational Cognitive Modeling | 5 | III-IV |
| CS-E4580 | Programming Parallel Computers | 5 | V |
| CS-E4850 | Computer Vision | 5 | I-II |
| CS-E4190 | Cloud Software and Systems | 5 | I-II |
* For students who already have completed an equivalent course as part of their previous studies, it's recommended to substitute this with another technical course. See the list of optional technical courses.
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Students taking a long
major can include a minor in elective studies. The minor is confirmed in the Personal Study Plan (HOPS).
More information on Aalto University’s minor subjects is in Aalto Minors page.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutiona studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages.
- If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies.
Human-Computer Interaction
With this degree, students can pursue careers in interactive technology where they lead design, engineering, development, research, or management. They are well-equipped to approach modern design problems, including technical challenges in intelligent systems, interface technologies, data analysis, interactive robots, human-centred development within industry and business contexts, and communications and networking. At the same time, they are knowledgeable about the human, social, and organizational factors affecting the success of interactive systems. They know how to address them in practical interdisciplinary development processes in business context and can further apply tools, practices and processes of human-centred design. They have technical skills to experiment and prototype innovative interactions as well as the meta-cognitive skills to drive visions of interactive technology, critically evaluate different approaches to interaction, and to develop competences further by following advanced research literature.
Code: SCI3097
Extent: Long (60 credits) or compact (40 credits) major. Students taking a compact major also have to take a minor (20-25 cr). Students taking a long major may include an optional minor in their elective studies.
Responsible Professor: Lauri Savioja
Appreviation: HCI
School: School of Science (coordinator) and Electrical Engineering
Name of the major in Finnish: Ihmisen ja tietokoneen vuorovaikutus
Name of the major in Swedish: Människa-datorinteraktion
Available study tracks:
- Human-Centred Design
- Intelligent and Interactive Systems
- XR and Blended Interaction
- Societal Computing
The major consists of common courses that are the same for each track. In addition, students need to select one track and take the compulsory courses of that track. Correspondingly, the students will select optional courses of the track to complete the major, up to 40 credits for a compact major, and up to 60 credits for a long major.
In addition, it is expected that students have studied the basics of human-computer interaction by taking a respective course such as the bachelor-level CS-C3120 Human-Computer Interaction as that is a recommended prerequisite course in multiple courses of the major.
Professor in charge: Marko Nieminen
Extent: Long (60 ECTS) or compact (40 ECTS) as HCI track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Objectives
The Human-Centred Design track has its focus on methods and practices which are applied in software and service development projects and organisations. The aim is to equip the students with knowledge and skills to create high-quality software considering end-users’ expectations and requirements. The contents of the courses, assignments, and seminars address the development of digital services from the definition, construction, and evaluation viewpoints delivering a balanced methodological toolbox for the student to apply in multi-disciplinary commercial and industrial service and software development contexts. The courses provide framing on human-centred design processes and cover user experience analysis, usability engineering, and user interface development.
| Code | Course name | ECTS credits | Teaching |
|---|---|---|---|
Major common courses (min 20 ECTS) |
|||
Select at least 15 ECTS |
|||
| CS-E5010 | Research Methods: Foundations* | 3 | I |
| CS-E5011 | Research Methods: Case studies & Design Science * | 2 | II |
| CS-E5012 | Research Methods: AI-based Data Synthesis & Analysis* | 2 | II |
| CS-E4900 | User-Centred Methods for Product and Service Design | 5 | I-II |
| ELEC-D7011 | Human Factors Engineering | 5 | V |
Select at least 5 ECTS |
|||
| CS-E5051 | Seminar in Human-Computer Interaction** | 5 | Varies |
| CS-E5052 | Special Course in Human-Computer Interaction*** | 1-10 | Varies |
| CS-E5053 | Individual Studies in Human-Computer Interaction | 1-10 | Agreed with a teacher |
Compulsory courses 14 ECTSFor Study track: Human-Centred Design |
|||
| CS-E5220 | User Interface Construction | 5 | II |
| CS-E5230 | Collaborative Evaluation of Interactive Systems | 5 | IV-V |
| CS-E5252 | Creative Digital Concept Design | 4 | III |
Optional courses (Select 0-26 ECTS) |
|||
| CS-C3150 | Software Engineering**** | 5 | I-II |
| CS-E4940 | Requirements Engineering | 5 | III-V |
| MUO-E3060 | Interaction Design - User Interfaces | 6 | II |
| MUO-E3061 | Interaction Design - User Experience | 6 | II |
| MUO-E3065 | Design for Social Change | 6 | II |
| CS-E4200 | Emergent User Interfaces | 5 | III-V |
| AXM-E5012 | Science of Game Design | 3 | II |
| CS-E4460 | WWW Applications | 5 | I-II |
| ELEC-E7852 | Computational Design and Interaction | 5 | II |
| CS-C3180 | Software Design and Modelling | 5 | I-II |
| CS-E4930 | Software Processes and Projects | 5 | III-V |
| CS-E4960 | Software Testing and Quality Assurance | 5 | I-II |
| CS-E5007 | Seminar in Software Engineering***** | 5 | Varies |
| CS-E4271 | Cross-Platform Development | 5 | I-II |
| TU-E1120 | Strategic Management of Technology and Innovation | 5 | III-IV |
*With CS-E5010, students must choose either CS-E5011 OR CS-E5012. Also both CS-E5011 AND CS-E5012 can be included in the major, if there is room for both courses.
** Course code varies and has additional number in the end (CS-E5051xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
*** Course code varies and has additional number in the end (CS-E5052xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
**** Note: This is a bachelor-level course and a prerequisite for many advanced courses in the area of software engineering.
***** Course code varies and has additional number in the end (CS-E5007xx). Check this in Sisu.
Professor in charge: Antti Oulasvirta
Extent: Long (60 ECTS) or compact (40 ECTS) as HCI track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Objectives
This track focuses on systems that utilize AI and machine learning (ML) to enhance interaction for people, be that for example in a chatbot, virtual reality, robots, or computer games. This track has a focus on computational and engineering methods for computing systems that utilize state-of-the-art AI/ML methods. Students learn how to process user data, design and adapt interfaces, and create new user experiences using such methods. The compulsory courses introduce engineering and theoretical principles of such systems, while the optional courses offer a deep dive into core methods and allow a specialization into an application domain.
| Code | Course name | ECTS credits | Teaching |
|---|---|---|---|
Major common courses (min 20 ECTS) |
|||
Select at least 15 ECTS |
|||
| CS-E5010 | Research Methods: Foundations* | 3 | I |
| CS-E5011 | Research Methods: Case studies & Design Science * | 2 | II |
| CS-E5012 | Research Methods: AI-based Data Synthesis & Analysis* | 2 | II |
| CS-E4900 | User-Centred Methods for Product and Service Design | 5 | I-II |
| ELEC-D7011 | Human Factors Engineering | 5 | V |
Select at least 5 ECTS |
|||
| CS-E5051 | Seminar in Human-Computer Interaction** | 5 | Varies |
| CS-E5052 | Special Course in Human-Computer Interaction*** | 1-10 | Varies |
| CS-E5053 | Individual Studies in Human-Computer Interaction | 1-10 | Agreed with a teacher |
Compulsory courses 20 ECTSFor Study track: Intelligent and Interactive Systems |
|||
| CS-E5220 | User Interface Construction | 5 | II |
| ELEC-E7852 | Computational Design and Interaction | 5 | II |
| CS-E4200 | Emergent User Interfaces | 5 | III-IV |
| ELEC-E7263 | Ambient Intelligence - Communications and Sensing | 5 | I-II |
Optional courses, long major, select 0-26 ECTS |
|||
| CS-E4840 | Information Visualization | 5 | IV |
| CS-E4460 | WWW Applications | 5 | I-II |
| ELEC-E8125 | Reinforcement Learning | 5 | I-II |
| CS-E4890 | Deep Learning | 5 | III-IV |
| CS-E5710 | Bayesian Data Analysis | 5 | I-II |
| CS-C3100 | Computer Graphics | 5 | I-II |
| ELEC-E5680 | Virtual Acoustics | 5 | III |
| CS-E4850 | Computer Vision | 5 | I-II |
| CS-E4150 | Digital Health and Human Behavior | 5 | II |
| AXM-E5012 | Science of Game Design | 3 | II |
| CS-E4460 | WWW Applications | 5 | I-II |
| ELEC-E7840 | Smart Wearables | 6 | III-IV |
| AXM-E0403 | Coding Virtual Worlds | 6 | I |
| ELEC-E7770 | Computational Cognitive Modeling | 5 | III-IV |
| ELEC-E5500 | Speech Processing | 5 | I |
*With CS-E5010, students must choose either CS-E5011 OR CS-E5012. Also both CS-E5011 AND CS-E5012 can be included in the major, if there is room for both courses.
** Course code varies and has additional number in the end (CS-E5051xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
*** Course code varies and has additional number in the end (CS-E5052xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
Professor in charge: Yu Xiao
Extent: Long (60 ECTS) or compact (40 ECTS) as HCI track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Objectives
This track focuses on extended reality (XR) and blended technologies, which are radically changing the way computing is used and experienced. These technologies can be used to augment environments and create entirely new immersive experiences with the help of interactive technology like head-up displays, wearable sensors and haptic devices. This track is designed to equip students with cutting-edge knowledge and skills in this rapidly evolving field area, focusing on the development and evaluation of XR experience, applications and devices. This multidisciplinary track merges technology, design, and human-computer interaction to explore XR technologies, including virtual reality, augmented reality and mixed reality, and wearable computing. Through the courses, students learn how to build applications for breakthough areas such as education, entertainment, healthcare, and manufacturing.
| Code | Course name | ECTS credits | Teaching |
|---|---|---|---|
Major common courses (min 20 ECTS) |
|||
Select at least 15 ECTS |
|||
| CS-E5010 | Research Methods: Foundations* | 3 | I |
| CS-E5011 | Research Methods: Case studies & Design Science * | 2 | II |
| CS-E5012 | Research Methods: AI-based Data Synthesis & Analysis* | 2 | II |
| CS-E4900 | User-Centred Methods for Product and Service Design | 5 | I-II |
| ELEC-D7011 | Human Factors Engineering | 5 | V |
Select at least 5 ECTS |
|||
| CS-E5051 | Seminar in Human-Computer Interaction** | 5 | Varies |
| CS-E5052 | Special Course in Human-Computer Interaction*** | 1-10 | Varies |
| CS-E5053 | Individual Studies in Human-Computer Interaction | 1-10 | Agreed with a teacher |
Compulsory courses 16 ECTSFor Study track: XR and Blended Interaction |
|||
| CS-E5230 | Collaborative Evaluation of Interactive Systems | 5 | IV-V |
| CS-E4200 | Emergent User Interfaces | 5 | III-V |
| AXM-E0404 | Designing and Creating Virtual Worlds**** | 6 | I-II |
Optional courses (Select 0-24 ECTS) |
|||
| MEC-E3020 | Methods in Early Product Development | 3 | II |
| ELEC-E7840 | Smart Wearables | 6 | III-IV |
| ELEC-E7845 | Smart Wearables II | 6 | I-II |
| CS-E4890 | Deep Learning | 5 | III-IV |
| CS-C3100 | Computer Graphics | 5 | I-II |
| ELEC-E5680 | Virtual Acoustics | 5 | III |
| CS-E5220 | User Interface Construction | 5 | II |
| CS-E4850 | Computer vision | 5 | I-II |
| MUO-E3061 | Interaction Design - User Experience | 6 | II |
| AXM-E0403 ELEC-A7151 |
Coding Virtual Worlds OR Object oriented programming with C++ |
6 5 |
I I-II |
*With CS-E5010, students must choose either CS-E5011 OR CS-E5012. Also both CS-E5011 AND CS-E5012 can be included in the major, if there is room for both courses.
** Course code varies and has additional number in the end (CS-E5051xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
*** Course code varies and has additional number in the end (CS-E5052xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
**** Students are expected to complete AXM-E0403 or similar programming courses first
Professor in charge: Juhi Kulshrestha
Extent: Long (60 ECTS) or compact (40 ECTS) as HCI track. Students taking a compact major take also a minor (20-25 credits). Students taking a long major may include an optional minor in their elective studies.
Objectives
The Societal Computing track examines the reciprocal relationship between computation and society. It is organized around two complementary perspectives: computation of society, which focuses on measuring, modeling, and understanding social phenomena through digital traces, network data, and behavioral analytics; and computation for society, which emphasizes the design, application and evaluation of computational systems to address societal challenges such as health, equity, and sustainability.
| Code | Course name | ECTS credits | Teaching |
|---|---|---|---|
Major common courses (min 20 ECTS) |
|||
Select at least 15 ECTS |
|||
| CS-E5010 | Research Methods: Foundations* | 3 | I |
| CS-E5011 | Research Methods: Case studies & Design Science * | 2 | II |
| CS-E5012 | Research Methods: AI-based Data Synthesis & Analysis* | 2 | II |
| CS-E4900 | User-Centred Methods for Product and Service Design | 5 | I-II |
| ELEC-D7011 | Human Factors Engineering | 5 | V |
Select at least 5 ECTS |
|||
| CS-E5051 | Seminar in Human-Computer Interaction** | 5 | Varies |
| CS-E5052 | Special Course in Human-Computer Interaction*** | 1-10 | Varies |
| CS-E5053 | Individual Studies in Human-Computer Interaction | 1-10 | Agreed with a teacher |
Compulsory courses 15 ECTSFor Study track: Societal Computing |
|||
| CS-E4150 | Digital Health and Human Behavior | 5 | II |
| CS-E4730 | Computational Social Science | 5 | IV-V |
| CS-E5485 | Algorithms and Society | 5 | 2026-2027: no teaching, 2027-2028: I |
Optional courses (Select 0-25 ECTS) |
|||
| CS-E4840 | Information Visualization | 5 | IV |
| CS-E5700 | Hands-on Network Analysis | 5 | IV-V |
| CS-E5740 | Complex Networks | 5 | I-II |
| CS-E5775 | Complex Systems | 5 | I |
| CS-E5490 | Technology and Power | 5 | I |
| ELEC-E5500 | Speech Processing | 5 | I |
| MUO-E3065 | Design for Social Change | 6 | II |
*With CS-E5010, students must choose either CS-E5011 OR CS-E5012. Also both CS-E5011 AND CS-E5012 can be included in the major, if there is room for both courses.
** Course code varies and has additional number in the end (CS-E5051xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
*** Course code varies and has additional number in the end (CS-E5052xx). Check these from Sisu. If there is room, this course can be included multiple times in the major.
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Students taking a long
major can include a minor in elective studies. The minor is confirmed in the Personal Study Plan (HOPS).
More information on Aalto University’s minor subjects is in Aalto Minors.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages.
- If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies.
Machine Learning, Data Science and Artificial Intelligence (Macadamia)
The major in Machine Learning, Data Science and Artificial Intelligence (Macadamia) gives a strong basic understanding of modern computational data analysis and modelling methodologies. It builds on the strong basic research at the Departments of Computer Science and Information and Communications Engineering. The methods of machine learning and data mining are applicable and needed in a wide variety of fields ranging from artificial intelligence to process industry, mobile communications and social networks. Recent spearhead research areas include deep learning, probabilistic machine learning, federated learning, bioinformatics, computational health, natural language processing, computer vision, multimodal interfaces, and human-in-loop AI.
The major provides an excellent basis for doctoral studies as well as industrial research and development work. Teaching and supervision for Macadamia students is given by an enthusiastic and experienced group headed by world leaders in this research field who also participate in the activities of the Finnish Center for Artificial Intelligence (FCAI). Excellent Macadamia students can continue their studies in the Helsinki Doctoral Education Network in Information and Communication Technology (HICT).
- The student is able to formalize data-intensive problems in data science and artificial intelligence in terms of the underlying statistical and computational principles.
- The student is able to select and apply a suitable machine learning method to solve a problem in industry or academia.
- The student can interpret the results of a machine learning method, assess their credibility, and communicate the results to experts from different fields.
- The student can implement state-of-the-art machine learning methods, and design and implement novel methods by modifying existing approaches.
- The student understands the theoretical foundations of the machine learning field to the extent of being able to follow research in the field.
- The student is familiar with ethical principles and techniques intended to inform the development and responsible use of artificial intelligence technology.
Code: SCI3044
Extent: Long major (60 credits). Compact major is not offered. Students who want to take a minor are encouraged to include it in elective studies.
Responsible Professor: Pekka Marttinen
Abbreviation: Macadamia
School: School of Science
Name of the Major in Finnish: Koneoppiminen, datatiede ja tekoäly
Name of the major in Swedish: Maskininlärning, datavetenskap och artificiell intelligens
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
Compulsory courses 15 ECTS |
|||
| CS-E4715 | Supervised Machine Learning | 5 | I-II / 1 |
| CS-E4890 | Deep Learning | 5 | III-IV / 1 |
| CS-E4891 | Deep Generative Models | 5 | IV-V/1 |
General Machine Learning, choose at least 20 ECTS |
|||
| CS-E5710 | Bayesian Data Analysis | 5 | I-II/1 or 2 |
| CS-E4650 | Methods of Data Mining | 5 | I-II/1 or 2 |
| CS-E4800 | Artificial Intelligence | 5 | III-IV/1 |
| CS-E5795 | Computational Methods in Stochastics | 5 | I-II / 1 |
| CS-E4825 | Probabilistic Machine Learning | 5 | III-IV / 1 |
| CS-E4740 | Federated Learning | 5 | IV-V / 1 |
| CS-E4895 | Gaussian Processes | 5 | IV-V / 1 |
| CS-E4840 | Information Visualization | 5 | IV/1 or 2 |
| CS-E4850 | Computer Vision | 5 | I-II / 2 |
| CS-E4855 | Seminar on Large Language Models | 5 | I-II |
| ELEC-E8125 | Reinforcement Learning | 5 | I-II / 2 |
Choose 0-25 ECTS to complete the long major (60 ECTS) * |
|||
| Bioinformatics and Digital Health | |||
| CS-E5866 | Computational Genomics | 5 | II / 1 |
| CS-E5885 | Modeling Biological Networks | 5 | III / 1 |
| CS-E4885 | Machine Learning in Biomedicine | 5 | I-II / 2 |
| CS-E5875 | High-Throughput Bioinformatics | 5 | IV / 1 |
| CS-E4150 | Digital Health and Human Behavior | 5 | II / 2 |
| Speech and Language | |||
| ELEC-E5500 | Speech Processing | 5 | I / 1 |
| ELEC-E5550 | Statistical Natural Language Processing | 5 | III-IV / 1 |
| ELEC-E5531 | Speech and Language Processing Seminar | 5 | III-IV / 1 |
| ELEC-E5510 | Speech Recognition | 5 | II / 2 |
| ELEC-E5541 | Special Assignment in Speech and Language Processing D | 5 | Agreed with a teacher |
| ELEC-E5523 | Speech Synthesis | 5 | IV-V / 1 |
| Large-scale Computational Methods | |||
| CS-E4580 | Programming Parallel Computers | 5 | V / 1 |
| CS-E3190 | Principles of Algorithmic Techniques | 5 | I-II / 2 |
| CS-E4690 | Programming Parallel Supercomputers | 5 | I-II / 2 |
| CS-E4685 | Machine Learning Applications in Universe Sciences | 5 | IV |
| CS-E4700 | Logic and Hard Computational Problems | 5 | I-II / 1 or 2 |
| Optimization | |||
| ELEC-E5424 | Convex Optimization | 5 | I-II / 2 |
| MS-E2122 | Non-linear Optimization | 5 | I-II / 2 |
| Courses with special arrangements | |||
| CS-E4003 | Special Assignment in Computer Science | 1-10 | Agreed with a teacher |
| CS-E4075 | Special Course in Machine Learning, Data Science and Artificial Intelligence D ** | 3-10 | Varies |
*Also other optional courses may be included per agreement with the person in charge of the major.
** Course code varies and has additional number in the end (CS-E4075xx). Check these from Sisu.
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a long major can include a minor in elective studies. The minor is confirmed in the Personal Study Plan (HOPS).
More information on Aalto University’s minor subjects is in Aalto Minors page.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages.
- If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies.
Signal Processing and Data Science (SPDS)
In Signal Processing and Data Science major you will learn to extract useful information, discover patterns, and make predictions from large amounts of signal or data, especially involving physical sensors and systems, like communication systems or energy distribution networks. With the learned toolbox of knowledge on signals and systems modelling, data science and machine learning, you can make devices, systems and entities smarter and more environmentally friendly. You get to apply your theoretical skills in wireless communications, radar systems, biomedical engineering and in various other fields. The major gives good grounds to work in companies, research organizations or to continue towards a doctoral degree.
Upon completion of the Major, the student will be able to:
- formalize problems in signal processing in terms of mathematical and statistical models and design and choose computational algorithms to efficiently solve them.
- effectively analyze, interpret, and derive insights from massive and diverse datasets using advanced data analysis and computational techniques.
- design, implement, and evaluate the performance of a signal processing method for solving a specific problem in ICT field.
- understand the theoretical foundations of signal processing and data science for being able to follow research in the field.
- possess technical and professional skills that enable them to take key roles in an industrial research and development tasks
Code: ELEC3049
Scope: long major (60 ECTS) or compact major (40 ECTS)
Responsible professor: Esa Ollila
Professors: Visa Koivunen, Sergiy Vorobyov, Risto Wichman, Esa Ollila, Filip Elvander
Abbreviation: SPDS
Language of the major: English
Name of the major in Finnish: Signaalinkäsittely ja datatiede
Name of the major in Swedish: Signalbehandling och datavetenskap
School: Electrical Engineering
The major consists of a compulsory part and an optional part. The major can be completed either as a long (60 ECTS) or compact (40 ECTS) major. Students taking a compact major take also an advanced studies level minor (20-25 ECTS). Students taking a long major may include an optional minor in their elective studies.
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
| ELEC-E0110 | Academic skills in master's studies | 3 | I-III English / 1st year |
| ELEC-E0210 | Master’s Thesis Process | 2 | I-V English / 2nd year |
| CS-E4715 | Supervised Machine Learning | 5 | I-II English / 1st year |
| ELEC-E5410 | Signal Processing for Communications | 5 | I-II English / 1st year |
| ELEC-E5431 | Large Scale Data Analysis D | 5 | III-IV English / 1st year |
| ELEC-E5440 | Statistical Signal Processing D | 5 | I-II English / 1st year |
| ELEC-E5810 | Biosignal Processing D | 5 | I English / 1st year |
| ELEC-E5481 | Machine Learning for Signal Processing | 5 | I-II English / 2nd year |
Choose 5 credits (compact major) or 25 credits (long major) |
|||
| ELEC-E5820 | Gaussian Signal Analysis D | 5 | IV-V English |
| ELEC-E5670 | Acoustical Measurements D | 5 | I English / 1st year |
| ELEC-E7263 | Ambient Intelligence – Communications and Sensing | 5 | I-II English |
| CS-E4890 | Deep Learning D | 5 | III-IV English |
| ELEC-E7340 | Machine Learning for Wireless Communications D | 5 | III – IV English / 1st year |
| ELEC-E5620 | Audio Signal Processing D | 5 | III-IV English |
| ELEC-E7120 | Wireless Systems | 5 | I English |
| CS-E5710 | Bayesian Data Analysis D | 5 | I-II English |
| CS-E5875 | High-Throughput Bioinformatics D | 5 | IV English |
| CS-E4825 | Probabilistic Machine Learning D | 5 | III-IV English |
| ELEC-E7211 | Digital Wireless Communication D | 5 | I-II English |
| ELEC-E5500 | Speech Processing | 5 | I English |
| ELEC-E5510 | Speech Recognition D | 5 | II English |
| ELEC-E5550 | Statistical Natural Language Processing D | 5 | III-IV English |
| ELEC-E8739 | AI in Health Technologies D | 5 | I-II English |
| ELEC-E8106 | Bayesian Filtering and Smoothing D | 5 | III-IV English |
| ELEC-E8740 | Basics of Sensor Fusion D | 5 | I-II English |
| ELEC-E5600 | Communication Acoustics | 5 | I English |
| CS-E4895 | Gaussian Processes D | 5 | IV-V English |
| CS-E4891 | Deep Generative Models D | 5 | IV-V English |
| ELEC-E5424 | Convex Optimization D | 5 | I-II English / 2nd year |
*Other courses can be included with permission from the responsible professor.
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Some majors have restrictions on the selection of a minor. Please check those from section Major 60 / 40 ECTS. The minor is confirmed in the Personal Study Plan (HOPS).
Students taking a long major can include a minor in elective studies.
More information on Aalto University’s minor subjects is in in Aalto Minors.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national
language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages. - If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies
Software Engineering
Digital products and services are crucial to economies, societies, and human well-being. For companies and other organizations, they offer exponentially expanding opportunities for new functionality and capabilities beyond traditional product boundaries. Software and Service Engineering students learn how to design, develop, and manage digital products and services that create business value and satisfy user needs within modern organizations. Students learn how to tackle wicked, real-world problems, taking human, societal, and organizational factors into account.
Students are encouraged to ensure they have technical knowledge of software development, e.g., by combining the major with a technical minor or by including technical courses, such as web software development or full-stack development, in their studies.
The major has two tracks making it possible allows students to specialize in software engineering or service design and engineering their studies towards technical, user-centred, or business-centred topics through course and minor subject choices.
Code: SCI3137
Extent: Long (60 credits) or compact major (40 credits). Students taking a compact major take also a minor (20–25 cr). Students taking a long major may include an optional minor in their elective studies.
Responsible professors: Fabian Fagerholm
Abbreviation: SE
School: School of Science
Name of the major in Finnish: Ohjelmistotuotanto
Name of the major in Swedish: Programvaruutveckling
SE offers both long and compact majors.
All the students majoring in software engineering take the major common courses (20-23 credits). In addition, they must choose at least two subject courses (10-20 credits) and at least one research methods or academic writing course (5-15 credits). It is strongly recommended that students also participate in the Portfolio in Software and Service Engineering course (CS-E4925).
The long major gives students the opportunity to specialize in software engineering to help them become software engineering experts in industry, as well as lays a good foundation for graduate studies. Students in the long major can tailor the major through selection of optional courses according to their interests in collaboration with their supervising professor.
The students take the major common courses (20-23 credits), subject courses (10-20 credits), and a research methods and academic writing package (5-15 credits). In addition, they take courses from the track optional course list. It is strongly recommended that students participate in the Portfolio in Software and Service Engineering course (CS-E4925).
The compact major aims at teaching students the main elements of software engineering to give them a sound foundation for future careers in industry.
The students take the major common courses(20-23 credits) subject courses (10-20 credits), and a research methods and academic writing package (5-15 credits). In addition, they take courses from the optional courses list. Students taking a compact major must have a minor (20-25 credits). It is strongly recommended that students also participate in the Portfolio course in Software Engineering (CS-E4925).
| Code | Course name | ECTS credits | Teaching |
|---|---|---|---|
Major common courses, 20-23 ECTS ECTS |
|||
| CS-C3150 | Software Engineering * | 5 | I-II |
| CS-E4900 | User-Centered Methods for Product and Service Design | 5 | I-II |
| CS-E4910 | Software Project 3 ** | 5-8 | I-V |
| CS-C3180 | Software Design and Modelling | 5 | I-II |
Subject courses, choose at least 10 ECTS |
|||
| CS-E4930 | Software Processes and Projects | 5 | III-V |
| CS-E4940 | Requirements Engineering | 5 | III-V |
| CS-E4950 | Software Architectures | 5 | III-V |
| CS-E4960 | Software Testing and Quality Assurance | 5 | I-II |
Research methods and academic writing package, choose at least 5 ECTS |
|||
| CS-E5010 | Research Methods: Foundations *** | 3 | I |
| CS-E5011 | Research Methods: Case Studies & Design Science *** | 2 | II |
| CS-E5012 | AI-based Data Synthesis & Analysis *** | 2 | II |
| CS-E5007 | Seminar in Software Engineering **** | 5 | Varies |
| CS-E5051 | Seminar in Human-Computer Interaction***** | 5 | Varies |
Optional courses, choose 0-25 ECTS |
|||
| CS-E4925 | Portfolio in Software and Service Engineering | 1-5 | I-V |
| Courses with a technical orientation | |||
| CS-E4400 | Design of WWW Services | 5 | I-II |
| CS-E4460 | WWW Applications | 5 | I-II |
| CS-E4190 | Cloud Software and Systems | 5 | I-II |
| Courses with an human-computer interaction orientation | |||
| CS-E5252 | Creative Digital Concept Design | 4 | III |
| CS-E5230 | Collaborative Evaluation of Interactive Systems | 5 | IV-V |
| CS-E4271 | Cross-Platform Development | 5 | I-II |
| CS-E5220 | User Interface Construction | 5 | II |
| Courses with an artificial intelligence / machine learning orientation | |||
| CS-E4075 | Special Course in Machine Learning, Data Science and Artificial Intelligence D **** | 3-10 | Varies |
| CS-E4715 | Supervised Machine Learning | 5 | I-II |
| CS-E4825 | Probabilistic Machine Learning | 5 | III-IV |
| CS-E4890 | Deep Learning | 5 | III-IV |
| CS-E4891 | Deep Generative Models | 5 | IV-V |
| CS-E4800 | Artificial Intelligence | 5 | III-IV |
| CS-E4805 | Trustworthy Artificial Intelligence | 5 | I-II |
| Courses with a business orientation | |||
| TU-C3015 | Introduction to Project Management | 5 | IV-V |
| 37E00200 | Strategic Information Technology Management | 6 | II |
| Other optional courses | |||
| CS-E5009 | Individual Studies in Software Engineering | 1-10 | Agreed with a teacher |
| CS-E5008 | Special Course in Software Engineering **** | 1-10 | Varies |
* If the course has been taken as part of the B.Sc. studies, it can be substituted with any optional courses of the track the student is studying student's chosen major. If the student has taken a similar course at another institution, the professor should be contacted for discussing possible substitution.
** Students taking the compact major are advised to take the course for 5 credits.
*** If choosing the research methods courses, students must choose CS-E5010 AND either CS-E5011 OR CS-E5012.
**** Course code varies and has additional number in the end (e.g. CS-E5057xx). Check these from Sisu.
***** For students whose optional courses have an HCI orientation. Not for students taking the compact major. Course code varies and has additional number in the end (CS-E5051xx). Check these from Sisu.
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Students taking a long major can include a minor in elective studies. The minor is confirmed in the Personal Study Plan (HOPS).
More information on Aalto University’s minor subjects is in Aalto Minors.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages.
- If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies.
Speech and Language Technology (SLT)
The purpose of the major is to provide the students with basics of speech and language processing and the ability to apply those in various fields of science and technology. Speech and language processing utilizes signal processing, mathematical modeling and machine learning for statistical language modeling and for speech analysis, synthesis, recognition, and coding. Speech and language technology is an interdisciplinary field where knowledge of signal processing and machine learning can be combined with the modelling and measuring of human behavior, for example, in speech production and perception. Recent applications and research priorities are, for example, speech recognition and synthesis, dictation, subtitling, machine translation, language learning, large-scale video data indexing and retrieval, speech coding and quality improvement as well as medical research of the human voice.
This major offers excellent opportunities also for postgraduate studies.
Code: ELEC3068
Scope: long major (60 ECTS) or compact major (40 ECTS)
Responsible professor: Mikko Kurimo
Professors: Paavo Alku, Tom Bäckström, Lauri Juvela
Abbreviation: SLT
Language of the major: English
Name of the major in Finnish: Puhe- ja kieliteknologia
Name of the major in Swedish: Tal- och språkteknologi
School: Electrical Engineering
The major consists of a compulsory part and an optional part. The major can be completed either as a long (60 ECTS) or compact (40 ECTS) major. Students taking a compact major also take an advanced studies level minor (20-25 ECTS). Students taking a long major may include an optional minor in their elective studies.
| Code | Course name | ECTS | Teaching |
|---|---|---|---|
| CS-E4715 | Supervised Machine Learning D | 5 | I-II English / 1st year |
| ELEC-E5500 | Speech Processing | 5 | I English / 1st year |
| ELEC-E0110 | Academic Skills in Master’s Studies | 3 | I-III English / 1st year |
| ELEC-E5510 | Speech Recognition D | 5 | II English / 1st year |
| ELEC-E5523 | Speech Synthesis D | 5 | IV-V English / 1st year |
| ELEC-E5531 | Speech and Language Processing Seminar V D | 5 | I-Summer English |
| ELEC-E5550 | Statistical Natural Language Processing D | 5 | III-IV English / 1st year |
| ELEC-E0210 | Master’s Thesis Process | 2 | I-V English / 2nd year |
Choose 5 credits (compact major) or 25 credits (long major) |
|||
| ELEC-E5410 | Signal Processing for Communications | 5 | I-II English / 1st year |
| ELEC-E5431 | Large Scale Data Analysis D | 5 | III-IV English |
| ELEC-E5620 | Audio Signal Processing D | 5 | III-IV English |
| CS-E5710 | Bayesian Data Analysis D | 5 | I-II English |
| ELEC-E5600 | Communication Acoustics | 5 | I English |
| CS-E5795 | Computational Methods in Stochastics D | 5 | I-II English |
| CS-E4850 | Computer Vision D | 5 | I-II English |
| CS-E4890 | Deep Learning D | 5 | III-IV English |
| CS-E4891 | Deep Generative Models D | 5 | IV-V English |
| ELEC-E5424 | Convex Optimization D | 5 | I-II English |
| CS-C3120 | Human-Computer Interaction | 5 | I-II English |
| CS-E4825 | Probabilistic Machine Learning D | 5 | III-IV English |
| ELEC-E5440 | Statistical Signal Processing D | 5 | I-II English |
| ELEC-E5481 | Machine Learning for Signal Processing | 5 | I-II English |
| ELEC-E5541 | Special Assignment in Speech and Language Processing V D | 1–10 | I - Summer English |
| CS-E4075 | Special Course in Machine Learning, Data Science and Artificial Intelligence D | 3-10 | I-Summer English |
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 must be a professor in Aalto University. The thesis advisor(s) can be from a company or from another university. 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.
Read more about writing the master's thesis under Thesis.
Students taking a compact major must have a minor (20–25 credits). Some majors have restrictions on the selection of a minor. Please check those from section Major 60 / 40 ECTS. The minor is confirmed in the Personal Study Plan (HOPS).
Students taking a long major can include a minor in elective studies.
More information on Aalto University’s minor subjects is in in Aalto Minors.
As elective studies, students can complete a minor and/or take individual courses. Individual elective courses can also be taken from other programmes at Aalto University or other Finnish universities through cross-institutional studies (RIPA) agreements of the CCIS programme.
Entrepreneurial and multidisciplinary Aalto studies are recommended. Foreign students are encouraged to take Finnish courses.
Also studies completed abroad during student exchange can be included in the elective studies (exchange studies can also form an international minor or be included in the major).
Work experience completed in Finland or abroad can also be included in elective studies (SCI students and ELEC’s HCI major students 1-10 credits, other ELEC students 2-5 credits). If students include course JOIN-A0003 Contributing in Community (3 cr) in their master’s degree, only 7 credits of practical training is accepted in the degree. More information about practical training you can find at Other studies.
In general, elective studies must be university or university of applied sciences level studies that fulfill the degree requirements and, in general, studies that are offered as degree studies at the university in question. Universities also offer courses that are targeted for a larger audience. The suitability of these studies is evaluated taking into consideration the learning outcomes of the programme and the aims of the master of science (technology) degree.
Elective studies require separate approval through the Personal Study Plan (HOPS).
Language studies
If you have compulsory language studies in your master's degree, they are included in the
elective studies.
- If you have completed your bachelor's degree in Finland (in Aalto or in another higher education institute), you have fulfilled the compulsory language requirements in the respective degree or received the exemption. You do not need to complete language studies in the master's degree.
- If your language of education is Finnish or Swedish and you have completed your bachelor’s degree outside of Finland, you must demonstrate proficiency in national languages by writing the maturity test in your language of education (Finnish or Swedish) and complete the language proficiency tests (2 ECTS) in the other national
language. Read more about the language of education here. You may also apply for an exemption of demonstrating proficiency in national languages. - If you have completed your bachelor’s degree outside of Finland, you are required to complete only 3 ECTS in one foreign language (including both oral (o) and written (w) proficiency). Students, whose language of education is not Finnish or Swedish, may alternatively complete an elementary course in Finnish or in Swedish. The courses in national languages can be at any level on CEFR scale.
Language studies are included in students’ elective studies and are agreed in the personal study plan (HOPS). Language Centre offers the language studies