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 interested in pursuing doctoral studies after their M.Sc. degree can easily transfer to the Helsinki Doctoral Education Network in Information and Communications Technology (HICT). Students acquire professional language and communication skills. All students are encouraged to include international, multidisciplinary, and entrepreneurial components as part of their studies.

Code: ELEC3030
Credits: Long (60 credits) or compact (40 credits) major
Professor in charge: Tapio Lokki (ELEC)
Professors: Ville Pulkki (ELEC), Lauri Savioja (SCI), Vesa Välimäki (ELEC)
Abbreviation: AAT
Pääaine suomeksi: Akustiikka ja audioteknologia
Huvudämne på svenska: Akustik och ljudteknik
School: Electrical Engineering (coordinator) and Science

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 in 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. The fields together constitute the field of communication acoustics, where there exists always a human listener at the end of the acoustic communication channel. Digital signal processing is currently an important tool in acoustics and audio engineering, and the teaching also emphasizes the understanding of its general principles and of 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 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 University 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.

The major can be completed either as a long (60 cr) major or a compact (40 cr) major. Students taking the compact major are required to also take a master level minor (20-25 cr). Students taking the long major may include an optional minor in their elective studies.

The major consists of 35 cr of compulsory courses and 5 or 25 cr of optional courses depending on the choice between long and compact major.

All the major courses 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.

Courses

You can view your degree structure and information on courses and study modules in Sisu (sisu.aalto.fi) once you’ve made a HOPS study plan (Sisu Help).  
 
Your study plan automatically shows the courses and study modules that are compulsory, i.e. those you are required to complete in order to graduate. For your elective (optional) studies module, you can find courses by using the search function either in Sisu’s ‘selection assistant’ or on the Search page (click Search on the upper banner). 

You will find recommended study schedules under Planning your studies.

Departmental study advisors:

Antti Ojapelto, room 1143 (Maarintie 8), room B333 (Konemiehentie 2), tel. +358 50 560 9741, [email protected]

Janani Fernandez, [email protected] 

Timo Dönsberg, tel. +358 40 7532 046, [email protected]

Code: ELEC3029
Credits: Long major (60 credits)
Professor in charge: Riku Jäntti
Professors: Riku Jäntti, Jukka Manner, Heikki Hämmäinen, Raimo Kantola, Stephan Sigg, Tarik Taleb, Patric Östergård, Risto Wichman, Olav Tirkkonen, Jyri Hämäläinen, Antti Oulasvirta, Yu Xiao
Pääaine suomeksi: Tietoliikennetekniikka
Huvudämne på svenska: Datakommunikationsteknik
Abbreviation: CE
School: Electrical Engineering

The major in Communications Engineering gives a solid understanding of Internet, wireless and communications ecosystems - from concepts, technologies and methodologies perspective. Education includes both theoretical and practical aspects of Communications Engineering, preparing the students for a successful career in industry, research organizations or in postgraduate studies without forgetting the professional language and communications skills learned during the education. Students are encouraged to include international, multidisciplinary, and entrepreneurial components as part of their studies.

The major consist of compulsory part and optional part. The optional part offers five different expertise areas: Cloud and network services, Wireless communications, Wearable computing and ambient intelligence, Communications ecosystems and Human-centric Systems.

You can view your degree structure and information on courses and study modules in Sisu (sisu.aalto.fi) once you’ve made a HOPS study plan (Sisu Help).  
 
Your study plan automatically shows the courses and study modules that are compulsory, i.e. those you are required to complete in order to graduate. For your elective (optional) studies module, you can find courses by using the search function either in Sisu’s ‘selection assistant’ or on the Search page (click Search on the upper banner). 

Compulsory courses (30 cr)

Optional courses (30 cr)

Recommendation: Select 20 - 30  cr from one of the following expertise areas:

Cloud and network services

Wireless communications

Wearable computing and ambient intelligence

Communications ecosystems

Human-centric Systems

Other optional courses (Choose to fulfill 60 credits):

You will find recommended study schedules under Planning your studies.

Study Coordinator: Mika Nupponen

Email: [email protected]
Tel: +358 50 365 0542
Maarintie 8, room 2540

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

Computer Science major combines both theoretical and applied computer science. The faculty includes over 25 professors. The major has common core courses and four different tracks, which focus on algorithms, software systems, Web, and Big Data. In addition, the major offers a wide range of advanced courses. Students typically do their Master's thesis in industry. Students interested in postgraduate studies can also do their thesis in research projects of Aalto University.

Available study tracks:

• Algorithms, Logic, and Computation
• Big Data and Large-Scale Computing
• Software Systems and Technologies
• Web Technologies, Applications, and Science

Major core courses

The major consists of core courses, track compulsory courses, and major 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 have to select at least five courses from the major core course list, including the compulsory core course(s) defined by the track. The core courses can also be done as part of the Bachelor studies, which reduces the number of core course required at the Master level. 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.

Professor in charge:  Petteri Kaski
Other professors: Chris Brzuska, Parinya Chalermsook, Tomi Janhunen, Pekka Orponen, Jukka Suomela, Jara Uitto
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:  Algorithms

Objectives

The study track on Algorithms, Logic, and Computation equips you with a strong methodological foundation that covers the modelling, design, and analysis of advanced algorithms and computing systems. In addition to skills in advanced programming and automated reasoning, you gain understanding of the foundations of cryptography and computational complexity theory. Studies in the track form an excellent basis for pursuing a PhD degree, and competitively selected students can start working toward their PhD 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, and use computational techniques to verify and synthesise such systems.

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 have to select at least five courses from the major core course list, including the compulsory core course(s) defined by the track (bolded). The core courses can also be done as part of the Bachelor studies, which reduces the number of core course required at the Master level. 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).

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.

Major core courses, compulsory major core course bolded

Track compulsory courses (select at least three, 15 credits)

Track optional courses

Professor in charge: Linh Truong
Other professors: 
SCI: Alex Jung, Jaakko Lehtinen, Kai Puolamäki, Jari Saramäki, Jukka Suomela, Maarit Käpylä
ELEC: Visa Koivunen, Jorma Skyttä, Sergei Vorobyov, Risto Wichman, Esa Ollila
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.

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. Excellent students interested in pursuing doctoral studies after their M.Sc. degree can transfer to the Helsinki Doctoral Education Network in Information and Communications Technology (HICT).

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 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 have to select at least five courses from the major core course list, including the compulsory core course(s) defined by the track (bolded). The core courses can also be done as part of the Bachelor studies, which reduces the number of core course required at the Master level. 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).

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.

Major core courses, compulsory major core courses bolded

Track compulsory courses (select at least three, 15 credits)

Track optional courses

Professor in charge: Mario Di Francesco 
Other professors: Tuomas Aura, N. Asokan, Lauri Malmi, Antti Ylä-Jääski, Jukka Suomela, Petteri Kaski
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: SST

Objectives

The Software Systems and Technologies track covers a wide range of topics on software systems, including mobile and cloud computing, energy efficiency of computing, novel networking technologies, and pervasive applications built on top of this basic foundation. The focus of the program is on applied computer science building on a solid software systems technology background. In this track it is also possible to study advanced learning technologies for education.

The students graduating from the track will have a strong technical background on many of the modern core technologies for mobile and cloud based applications. Students interested in pursuing doctoral studies after their M.Sc. degree can easily transfer to the Helsinki Doctoral Education Network in Information and Communications Technology (HICT).

Learning Outcomes

The graduates of the Software Systems and Technologies track will be able to create and analyze large software systems. The main areas of software systems covered are mobile and cloud computing, energy efficiency of computing, novel networking, and pervasive applications. The track focuses on applied computer science building on a solid software systems background. It is also possible to study advanced learning technologies for education through this track.

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 have to select at least five courses from the major core course list, including the compulsory core course(s) defined by the track (bolded). The core courses can also be done as part of the Bachelor studies, which reduces the number of core course required at the Master level. 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).

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.

Major core courses, compulsory major core course bolded (min 25 credits)

Track compulsory courses (15 credits)

Track optional courses

Professor in charge: Petri Vuorimaa
Other professors: Eero Hyvönen
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 have to select at least five courses from the major core course list, including the compulsory core course(s) defined by the track (bolded). The core courses can also be done as part of the Bachelor studies, which reduces the number of core course required at the Master level. 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).

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.

Major core courses, compulsory major core courses bolded

Track compulsory courses

Track 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
Appreviation: Game
School: School of Science

Objectives

The objective of the major is to educate programmer-designers* that understand both technology and the player’s point of view, and can thus 1) participate in overall game design and 2) 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, 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 technical courses on computer graphics, machine learning, and artificial intelligence)
• Building a wide set of cross-disciplinary design, production, and teamworking skills (compulsory Deparment of Media courses, especially DOM-E5095 game project, during which multiple games are developed). 
• Deeper understanding of each student's specific areas of interest (large selection of elective courses that can be included in the personal study plan).

The Game Design and Production major is organized in collaboration with Media Lab Helsinki of Aalto ARTS, which has an M.A. in New Media “sibling major” with the same name. Computer and video games 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.

Courses

Major compulsory courses

^{*) Students with no previous knowledge in machine learning should take course CS-C3240 Machine Learning instead. The follow-up course can be included in elective studies.}

Recommended optional courses

(Students may also suggest others as game design is a multidisciplinary field).

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: Antti Oulasvirta (homepage)
Other professors: Perttu Hämäläinen, Janne Lindqvist, Elisa Mekler, Marko Nieminen, Tapio Takala, Giulio Jacucci (University of Helsinki/Computer Science)
Appreviation: HCI
School: School of Science (coordinator) and Electrical Engineering 

Objectives

Human-computer interaction is a field concerned with the design and study of interactive computing systems for human use. Experts in the field study opportunities in computing technology to innovate novel ways to use it, they design user interfaces and engineer the enabling hardware and software, and they produce empirical knowledge to inform decision- making concerning technology.

Master’s studies in Human-Computer Interaction (HCI) prepare future experts and leaders who use advanced methodology and technology to innovate and improve information technology for the benefit of people. The aim of our new HCI major is unique in Europe: It combines rigorous courses in computational and engineering disciplines, such as AI and machine learning, with spearheads in user interface technology and interface design, yet building supporting competences in interaction design, empirical research, and entrepreneurship. Highlights of the curriculum include:

• Skill set recognized globally in competitive industry positions and PhD programmes,especially in areas cross-cutting design, interaction, and AI
• An interdisciplinary orientation with strong emphasis on computer science and engineering but including contributions from psychology and design
• Competences complementing exact and engineering sciences, in particular in creative design, prototyping, and evaluation of interactive systems using advanced technologies
• Interaction with world-class research faculty across departments at Aalto as well as in the University of Helsinki
• Learning to learn in the area of HCI; a life-long learning attitude
• strong specialization on a technical topic and a capstone course supporting students to achieve their potential at internationally benchmarked level on realistic problems carried out with top players in the industry and academic
• Soft skills, including meta-cognitive skills, scientific literacy and writing skills, critical thinking, presentations, and teamwork.

The education builds on recognized research efforts on HCI in Aalto University and University of Helsinki and it ties to top education offered in the CCIS program. HCI research at Aalto University is globally recognized and ranked as #2 in Europe and #14 in the world (source: csrankings.org).

Learning Outcomes

With this degree, students can pursue careers where they lead design, research, or management. They are well-equipped to approach modern design problems including challenges in intelligent systems, concept creation, interface technologies, algorithms, data, modeling, and communications and networking. However, they are also knowledgeable about the human and social factors affecting the success of interactive systems. They know how to address them in practical interdisciplinary development processes in business context. 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.

Overall structure:

• Basics: Design thinking and methods for engineering and computer science students; User-centered methods, user research, and strategic usability in software engineering
• Computational and engineering specialization: Analysis, modeling, and computational solution of design problems; Data-driven design using computational methods (e.g. AI, machine learning, control, optimization, logic); Novel forms of interactive technologies and media; Interactive applications and systems, especially development and design; Interactive visual computing, such as augmented and virtual reality
• A capstone project and (optional) research immersion including interaction with worldclass faculty and companies.

The major covers four main topics: (1) empirical research, such as the study of user needs to elicit requirements for a product, (2) constructive research, such as the concept design, computational design, and prototyping techniques, (3) interface technology from algorithms to  electrical engineering perspectives, and (4) analytical and modeling-oriented research, such as a model explaining how choices in user interface design affect user performance. It also educates methods in user-centered design, including those for user research, sketching and prototyping, and evaluation. The courses cover a wide range of technical topics including input devices, interactive media, interaction techniques, interface technologies, interactive applications, social media, and multimodal interactive systems. Students learn both design thinking and the scientific basis of HCI in modeling, theories, and methods. As the curriculum progresses, they learn to apply their skills to increasingly more realistic problems. They are introduced to human factors, social sciences, business, and design. A lot of emphasis is put on ‘learning to learn’, improving the student’s ability to read, apply, and critically discuss scientific research in this area.

Student Experience

During the first year, students learn core methodologies and techniques in the design, study, and analysis of interaction. During the second year, they start to specialize on a technical topic. Students can flexibly build their study plans consisting of core and elective courses. The core courses provide a strong foundation in design, empirical methods, and theories of HCI. The elective courses allow a student to organize studies around technical topics in HCI, such as interactive graphics, mixed reality, user-centered software engineering, user interface software technologies, interaction techniques, interactive machine learning, interactive visualizations, computational design, usable security, and user interface technology. A reading group and a research immersion on advanced topics is offered to final-year students. During the last year, they complete a capstone project with an external client (industry or academic) and write a Master's thesis for a company or an academic group.

Courses

Major compulsory courses (min. 35 cr for the long major, min. 25 cr for the compact major)

 ^{*) You can omit this if you have a similar course in your previous studies.
**) Organized by the University of Helsinki. Students apply for this course through Flexible Study Right Agreement JOO.
***) You can replace this with something similar.}

In-depth specialization

In-depth specialization is custom-tailored and approved via HOPS. The student choose a list of specialization courses with the following constraints:

• An HCI course should be accompanied by a matching technical course from the offerings of CCIS. For example, to specialize in interactive machine learning, we recommend an extracourse on information visualization with an in-depth course on machine learning

Topics recommended for specialization include but are not limited to:

• Web technologies
• Speech recognition
• Robotics
• AR and VR
• CSCW and CMC
• Usable security
• Visual and interactive computing
• Machine learning and AI, including deep learning, reinforcement learning, probabilistic inference
• Interactive data analysis and visualization, including Bayesian data analysis
• Game design
• Ubiquitous computing
• Health technology
• Quality of Experience
• Neural and brain interfaces
• Accessibility
• User-centered software engineering

We also recommend the following in-depth seminar: 

Mandatory capstone course for both long and short majors is chosen according to focus on industry (CS-E5200) or research (ELEC-E7861). (Choose one or the other.)

 ^{*) Note that CS-E4900 User-Centered Methods for Product and Service Design is a prerequisite for Data-Driven Concept Design.}

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 Person: Senior University Lecturer Jorma Laaksonen
Professors:
SCI: Samuel Kaski, Rohit Babbar, Alexander Ilin, Alex Jung, Juho Kannala, Maarit Käpylä, Jouko Lampinen, Harri Lähdesmäki, Heikki Mannila, Pekka Marttinen, Jussi Rintanen, Juho Rousu, Arno Solin, Aki Vehtari
ELEC: Paavo Alku, Tom Bäckström, Mikko Kurimo
Abbreviation: Macadamia
School: School of Science

Objectives

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 research at the Department of Computer Science. The methods of machine learning and data mining are applicable and needed in a wide variety of fields ranging from process industry to mobile communications, social networks and artificial intelligence. Recent spearhead application areas include bioinformatics, computational linguistics, multimodal interfaces, and intelligent information access.

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. Excellent Macadamia students can continue their studies in the Helsinki Doctoral Education Network in Information and Communication Technology (HICT).

Learning Outcomes

1. The student is able to formalize data-intensive problems in data science and artificial intelligence in terms of the underlying statistical and computational principles.
2. The student is able to assess suitability of different machine learning methods for solving a particular new problem encountered in industry or academia, and apply the methods to the problem.
3. The student can interpret the results of a machine learning algorithm, assess their credibility, and communicate the results with experts of other fields.
4. The student can implement common machine learning methods, and design and implement novel methods by modifying the existing approaches.
5. The student understands the theoretical foundations of the machine learning field to the extent required for being able to follow research in the field.
6. The student understands the opportunities that machine learning offers in data science and artificial intelligence.

The students have to take the seven compulsory courses unless they already have the same knowledge.  In addition, they include courses from the major optional courses list, some of which can be taken multiple times.  Also other optional courses may be included per agreement with a professor in charge of the major.

Major compulsory courses 35-40 credits

Major optional courses (choose 20-25 credits)

^{Also other optional courses may be included per agreement with a professor in charge of the major.} 

Code: SCI3084
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: Tuomas Aura
Other professors: Mario Di Francesco, Janne Lindqvist, Linh Truong, Antti Ylä-Jääski 
Abbreviation: Security
School: School of Science

Study programme

Studies in the Security and Cloud Computing major give students a broad understanding of the latest and future technologies for secure mobile and cloud computing systems. Students will gain both practical engineering knowledge and theoretical insights into secure systems engineering, distributed application development, network and service architectures, and cloud and mobile platforms. We believe in combining theoretical knowledge and security expertise with product development skills. The studies are also closely linked with research at Aalto University. 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

Security-major aims to educate professional engineers who are able to take on the most demanding R&D tasks and drive the development of future products and services. More specifically, the learning outcomes are the following:

• Students have the theoretical understanding of information security and practical skills for designing and analyzing secure computing systems.
• Students understand the architectural principles of distributed services and applications. They are able to design, analyze and implement distributed, cloud and mobile computing systems.
• Students have in-depth knowledge of their chosen thesis topicand are able to apply it to solving technical and scientific problems.
• Students have strong software development skills and other technical and professional skills that enable them to take key roles in an industrial research and development environment, and they are qualified to continue to doctoral studies in academia.

Structure and content

The major covers fundamental concepts, methods and the latest technologies on secure systems engineering, distributed application development, ubiquitous computing, network and service architectures, ubiquitous computing, and cloud and mobile computing platforms. The studies are closely bound to the research done by the teachers, for example, on the Internet of Things, pervasive and ubiquitous computing, cloud platforms and services, mobile platform security, and network security. Special attention is paid to security and privacy issues as they are critical requirements in developing and deploying services in open networks and distributed systems. The teaching methods combine theory with hands-on exercises and software development on cloud platform and mobile devices. Students also practice writing and presentation skills and learn to follow the latest research.

Learning methods

Engineers must be able to apply theoretical knowledge to real world engineering tasks. Therefore, the program combines theoretical studies with continuous hand-on exercises and projects where the new knowledge is applied. Much of the students’ time is spent on group and individual assignments that train problem solving, secure system design, and software engineering skills. In the courses that involve classroom teaching, it takes varied forms from traditional lectures and exercise sessions to discussion of group projects and student presentations. All students participate in a seminar course where students learn to write a technical or research article and present their own work.

The studies include opportunities for networking with local and European companies. Many of the teachers have industry background, and our partner companies contribute to some courses and projects. The partner companies also host summer interns, and majority of the master’s thesis projects are done in industry in paid projects

Major compulsory courses

These courses are compulsory, unless already included in the student’s previous studies. Students who have studied similar content at another university or have specific personal learning goals should contact the responsible professor of the major to discuss their personal study plan.

Major optional courses

Students should choose enough other master-level courses to meet the required number of credits for the major. The courses listed below are especially recommended. Please follow announcements about special courses with annually changing topics and teaching periods. Other master-level courses on relevant topics, including computer science, mathematics, communications technology and entrepreneurship may be included with prior agreement of the responsible professor of the major.

Code: ELEC3031
Extent: long major (60 cr) or compact major (40 cr)
Responsible professor: Mikko Kurimo
Professors: Paavo Alku, Tom Bäckström, Visa Koivunen, Esa Ollila, Jorma Skyttä, Sergiy Vorobyov, Risto Wichman
Abbreviation: SSLP
Pääaine suomeksi: Signaalin-, puheen- ja kielenkäsittely
Huvudämne på svenska: Signal-, tal- och språkbehandling
School: Electrical Engineering

The purpose of the major is to provide the students with basics of either signal processing or speech and language processing and the ability to apply those in various fields of science and technology.

Students focusing in signal processing are given a strong theoretical and methodological background of modern signal processing. This means a toolbox of knowledge on signals and systems modelling, representation through transforms, systems optimization and implementation. In signal processing physical world meets information. This means that the signals or data from physical world is typically acquired by sensors and signal processing reveals relevant information from it. Some emphasis is on the most recent research priorities in the field of signal processing in domains of data analysis and statistical inference and learning, communications as well as in representation of signals. In addition, students can obtain even deeper understanding of signal processing and adjacent sciences, or apply signal processing in other fields. Interesting applications include radar systems and networks, wireless communications, data science, statistical learning and inference, distributed sensing of physical phenomena and detecting and tracking changes, as well as analysis of technical (machine based) and social (human based) networks. For example, in a cyber-physical system, information and communications technology (ICT) are used to monitor and control a real-world physical system. The smart power grid is a prime example where signal processing methods are needed to improve energy distribution, production and utilization efficiency and consequently sustainability. Signal processing makes our devices smart and allows for solving essential problems of great societal impact.

Students focusing on speech and language processing are provided with the basics of this field and the ability to apply this knowledge in various fields of science and technology. Speech and language processing utilizes signal processing, mathematical modeling and machine learning for statistical language modeling, information retrieval and for speech analysis, synthesis, recognition and coding.  Speech and language processing is also 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.

The major offers two different study tracks: signal processing and data science, and speech and language processing. The tracks consist of a compulsory part and an optional part. Student must follow one of the study tracks. In the major there are three courses common to both tracks.

The major can be completed either as a long (60 cr) or compact (40 cr) major. Students taking a compact major take also a master level minor (20-25 cr). Students taking a long major may include an optional minor in their elective studies.

You can view your degree structure and information on courses and study modules in Sisu (sisu.aalto.fi) once you’ve made a HOPS study plan (Sisu Help). 

Your study plan automatically shows the courses and study modules that are compulsory, i.e. those you are required to complete in order to graduate. For your elective (optional) studies module, you can find courses by using the search function either in Sisu’s ‘selection assistant’ or on the Search page (click Search on the upper banner). 

See recommended study orders under Planning your studies.  

See recommended study orders under Planning your studies.  

Code: SCI3043
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: Casper Lassenius
Abbreviation: SSE
School: School of Science

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. Students of Software and Service Engineering 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 that 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 three tracks making it possible to specialize in software engineering, service design and engineering, or enterprise systems.

SSE offers both long and compact majors. The following tracks are available:

1. Software Engineering
2. Service Design and Engineering (SDE)
3. Enterprise Systems

All the students majoring software and service engineering take the major common courses (10 credits). In addition, they take courses according to their study track. It is strongly recommended that students also participate in the Portfolio in Software and Service Engineering course (CS-E4920)

Major common courses 10 credits

^{* 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. If the student has taken a similar course at another institution, the professor should be contacted for discussing possible substitution.}

Professor in charge: Casper Lassenius
Other professors: Jari Collin
Extent: Long (60credits) or compact major (40 credits). 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

For most companies and organizations, developing and managing information systems has become increasingly critical for how the companies create and capture value, how they work with partners and users, and how they secure competitive advantage. The Enterprise Systems track provides its students the knowledge, competences, and skills they will need to act successfully in the industry and society to tackle these challenges and opportunities.

Learning outcomes

After completing the track, the students should be able to understand the opportunities of digitalization in industrial applications and related domains and to turn these opportunities to actual business value by defining, creating, deploying, and managing relevant information systems. They will have the skills needed to work effectively in multidisciplinary teams including business and technology experts.

Structure

Students are expected to take the major common courses and track compulsory courses. In addition, they take courses from the track optional course list. It is strongly recommended that students also participate in the Portfolio in Software and Service Engineering course (CS-E4920).

Major common courses (10 credits)

Track compulsory courses (15 credits)

Track optional courses

^{* If any of these courses have been taken as part of the B.Sc. studies, they can be substituted with any elective courses of the track. If the student has taken similar courses at another institution, the professor should be contacted for discussing possible substitutions.} 

Professor in charge: Marjo Kauppinen and Marko Nieminen
Other professors: Johanna Kaipio
Extent: Compact (40 credits) or long (60 credits) major. Students taking a compact major also take a minor (20–25 credits). Students taking a long major may include an optional minor in their elective studies.
Abbreviation: SDE

Objectives

Digital services and software form an integral part of modern everyday life. The Service Design and Engineering (SDE) track is for students who want to specialise in developing human-centric digital services and analysing their impact on business and society.

The SDE track focuses on collaborative software and service design, where understanding customer and user needs is essential. The track provides theoretical and practical means for working with customers, users, and other stakeholders throughout the whole lifecycle of the service. Students learn to work in multidisciplinary teams where they create innovative, and commercially viable solutions. They apply user-centred and software engineering methods to support joint design and evaluation activities.

After completing their studies, students can work in industry, design and engineering companies, public organisations as well as in startups as product owners, software developers, user interface and interaction designers, usability specialists, user experience managers, service designers, project managers, and business analysts. The track provides a good starting point for doctoral studies. 

Learning outcomes

In the SDE track, students learn to

1. discover and analyse customer, user and business needs
2. apply methods  from software engineering, service design and user-centred design in practice
3. definean efficient design process for the needs of a company and projects
4. collaboratively develop digital services that create customer and business value
5. innovative service concepts in multidisciplinary teams
6. critically evaluate service concepts and digital services
7. build up a strong conceptual foundation for continuous learning.

Content and structure

Service Design and Engineering Compact Major 40 credits

The compact major of the SDE track consists of two major common courses. In addition to these courses, the Design Project is the only compulsory course. Students can also select courses from the track optional course list. It is strongly recommended that students also participate in Portfolio in Software and Service Engineering course (CS-E4920). Combined with personal discussions with responsible professors of the track, this course supports students in finding their individual study and career profile.

It is strongly recommended that students select a minor that emphasises multidisciplinarity. Students taking the SDE track who wish to focus on entrepreneurship are recommended to take the Startup Minor as their minor.

Major common courses (10 credits)

Track compulsory course (5 credits)

Track optional courses (20–25 credits)

^{In addition to the above, courses from the other tracks of the SSE major can be included as optional courses. Also other optional courses can be included per agreement with a professor in charge of the track.
') If any of these courses have been taken as part of the B.Sc. studies, they can be substituted with any elective courses of the track. In the case the student has taken similar courses at another institution, the professor should be contacted for discussing possible substitutions.} 

Service Design and Engineering Long Major 60 credits

The long major of the SDE track consists of two major common courses. In addition to these courses, the Design Project is the only compulsory course. Students can also select courses from the track optional course list. It is strongly recommended that students also participate in the course Portfolio in Software and Service Engineering (CS-E4920). Combined with personal discussions with responsible professors of the track, this course supports students in finding their individual study and career profile.

Students selecting the long major focus on various aspects of digital service design including user-centred design, business and customer analysis combined with software engineering. Students with a  long major have the possibility to tailor the major personally in collaboration with their supervising professor. Additionally, the long major lays a proper foundation for doctoral studies in the field.

Students taking the SDE track who wish to focus on entrepreneurship are recommended to take the Startup Minor as part of their elective studies.

Major common courses (10 credits)

Track compulsory course (5 credits)

Track optional courses (select 35–45 credits from the following)

Courses that strengthen the multidisciplinary contents of the studies are especially recommended. These include, for instance, the following courses. The student shall make sure that participating in those courses is possible.

^{Also other optional courses can be included per agreement with a professor in charge of the track.}

Professor in charge: Casper Lassenius
Other professors: Marjo Kauppinen
Extent: Long (60 credits) or compact (40 credits) major. Students taking a compact major also take a minor (20–25 credits). Students taking a long major may include an optional minor in their elective studies.

Objectives

Software is at the core of most developed economies and organizations. The software engineering track is intended for students who want to become proficient in developing and managing development of software systems and services in real-world organizations, big and small. 

The track combines theoretical studies with a large number of practical assignments done both in groups and as individuals, providing opportunities not only to understand but to apply the various methods and tools taught. Many of the assignments are either done for industrial customers representing real-life organizations or based on cases from industry. Many courses use lecturers from industry to provide practical viewpoints to the subjects studied.

Software engineering majors typically work in industry in roles such as Scrum Master, team lead, software architect, project manager, test lead, process engineer, or product owner. Students of software engineering are recommended to take a technical minor in computer science, but the major can also be fruitfully combined with e.g. strategic management, organizational development, or occupational psychology and leadership. The long major gives students the possibility to study software engineering more in-depth, giving the possibility to focus on a specific area of interest. This lays a good foundation for expert roles in industry, or for PhD studies in software engineering.

Learning outcomes

In the software engineering track, students learn the processes, methods and techniques used in professional software development in organizations and projects of various sizes. Core subjects include various software development activities, such as requirements engineering, design, implementation, testing and deployment, as well as supporting activities including project management, organizational development, and configuration management.

Software Engineering long major (60 credits)

The long major in software engineering gives students the opportunity to specialize in software engineering to help become software engineering experts in industry, as well as lays a good foundation for graduate studies. Students of the long major have the possibility to tailor the major personally in collaboration with their supervising professor.

The students take the major common courses and track compulsory courses. In addition, they take courses from the track optional course list. It is strongly recommended that students participate in Portfolio in Software and Service Engineering course (CS-E4920).

Major common courses (10 credits)

Track compulsory courses (15-18 credits)

Track optional courses

^{* If the course has been taken as part of the B.Sc. studies, it can be substituted with any optional courses of the track. In the case the student has taken similar courses at another institution, the professor should be contacted for discussing possible substitutions.
In addition to the above, courses from the other tracks of the SSE major can be included as optional courses. Also other optional courses can be included per agreement with a professor in charge of the track. 
It is recommended to take most of the software engineering specific courses (Software Engineering, Software Design and Modelling, Software Processes and Projects, Requirements Engineering, Software Architectures, and Software Testing and Quality Assurance) during the first year of studies. Their content is to be applied in practice on the Software Project 3 course during the second year.}

Software Engineering compact major 40 credits

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 (10 credits) and track compulsory courses (10–13 credits). In addition, they take courses from the track 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 and Service Engineering (CS-E4920).

Major common courses (10 credits)

Track compulsory courses (10-13 credits)

Track optional courses

^{* If the course has been taken as part of the B.Sc. studies, it can be substituted with any optional courses of the track. In the case the student has taken similar courses at another institution, the professor should be contacted for discussing possible substitutions.
In addition to the above, courses from the other tracks of the SSE major can be included as optional courses. Also other optional courses can be included per agreement with a professor in charge of the track.      
It is recommended to take most of the software engineering specific courses (Software Engineering, Software Design and Modelling, Software Processes and Projects, Requirements Engineering, Software Architectures, and Software testing and Quality Assurance) during the first year of studies. Their content is to be applied in practice on the Software Project 3 course during the second year.}

Students who have a long major (60 credits) choose 30 credits of elective studies. Students who have a compact major must choose a minor (20-25 cr) and 25-30 credits of elective studies. Altogether major, possible minor and electives have to be 90 credits.

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 Flexible Study Right (JOO).

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 max. 10 credits, ELEC students max 5 credits, excluding HCI major students). More information about practical training you can find under 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 degree that the courses are planned to be included in.

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 are encouraged to include a minor in elective studies. Bachelor level minors may be accepted. The minor is confirmed in the Personal Study Plan (HOPS).

More information on Aalto University’s minor subjects is in Aalto Minors page.

Compulsory language studies are included as part of the Finnish bachelor’s degree for students who have studied in Finland and whose language of education is Finnish or Swedish. If the language studies have not been completed in the student’s bachelor’s degree, the student must take 2 ECTS in the second national language and 3 ECTS in one foreign language, including both oral and written proficiency.

Students who have received their education in a language other than Finnish or Swedish, or received their education abroad, are required to complete only 3 ECTS in one foreign language, including both oral and written proficiency. Relevant courses (marked with 'o' and 'w') are offered by the Aalto University Language Center.

Students who have received their education abroad and who already have excellent command of English (e.g. English as their first language) may choose 3 credits of Finnish courses instead, hence not covering the requirement of oral/written proficiency but meeting the language requirement of the degree. If this applies to you, please contact the student services for further advice.

Compulsory Foreign Language studies are offered by Aalto University Language centre.

School of Science:
Application for the exemption from the obligatory foreign language requirement