KTH Royal Institute of Technology
MSc ICT Innovation KTH
Stockholm, Sweden
MSc
DURATION
2 years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
Aug 2027
TUITION FEES
SEK 360,000 *
STUDY FORMAT
On-Campus
* for non-EU/EEA/Swiss | no tuition fee for citizens of EU/EEA country or Switzerland
Key Summary
About: The MSc ICT Innovation at KTH mixes 90 ECTS technical ICT study with 30 ECTS innovation and entrepreneurship. You choose one of five tracks. The programme includes an industry-based master’s project, internship, and a 6 ECTS I&E project. It's a two-year, 120 ECTS Master of Science taught in English.
Career Outcomes: The programme opens opportunities in start-ups, research-driven organisations, and advanced IT businesses. It prepares you for product and business management, system and software development, consulting, data science, UX or cloud/HPC engineering. Industry projects and internships build practical skills, networks, and entrepreneurial experience for specialist or managerial global careers.
The master's programme ICT Innovation combines technical competencies with skills in innovation and entrepreneurship. The programme strongly focuses on integrating education, research and business modules in its curriculum, with active industry involvement. Students choose one of six technical specialisation tracks. Graduates work with system and software development, product management, business development, start-ups and consulting.
ICT Innovation at KTH
The main subjects of the master's programme in ICT Innovation are Computer Science and Electrical Engineering. The programme combines advanced technical education in information and communication technology (90 ECTS) with business-oriented courses focusing on innovation and entrepreneurship (30 ECTS).
The Innovation and Entrepreneurship (I&E) education within the ICT Innovation master’s programme equips future ICT engineers with an entrepreneurial mindset to support digital transformation. The I&E courses are compulsory for all students in the programme, regardless of their selected track.
The programme offers five tracks that provide further technical specialisation:
Autonomous Systems
The Autonomous Systems track is a combination of computer science and mechatronics engineering. The track is well aligned with market demand in the automobile, manufacturing, logistics, shipping, mining, and recycling industries. Autonomous software systems are also widely spreading in application areas, such as media, finance, customer service, and healthcare.
Data Science
The Data Science track concerns methods and technology for collecting, organising and analysing data to generate new knowledge. This includes implementing and applying machine learning algorithms, platforms for distributed handling of extensive data, large-scale machine learning, algorithms and systems for descriptive and predictive modelling, including the analysis of complex data such as networks, text and images.
Visual Computing and Communication
The Visual Computing and Communication track combines computer science and information technology in the areas of image processing and communication, image analysis, computer vision, computer graphics, augmented reality, visualisation, visual analytics, as well as web-based and network applications.
Human Computer Interaction and Design
The Human-Computer Interaction and Design track takes an interdisciplinary user-centred design approach. It combines human aspects (cognitive, aesthetic, and sensory-motor levels) with technological and business aspects to create new products and services with great usability and user experience, according to customer demand.
Cloud and Network Infrastructures and HPC
The Cloud and Network Infrastructures and HPC track covers the design, management, and operation of communication networks, as well as HPC, cloud services, deployment models, and application development. The track also addresses future directions of cloud computing, for example, in the fields of edge and fog computing, as well as blockchains and distributed ledger applications.
A key component in all specialisations of ICT Innovation is the integrated combination of a master’s degree project (30 ECTS), an “internship” (which should be included in the degree project credits) and an I&E project (6 ECTS). The industry-based degree project (typically integrated with the "internship") is well integrated with the I&E minor and technical majors.
The programme covers two years of study at KTH in Stockholm. However, students who would like to attend the second year of the programme abroad can do so under the EIT Digital scheme, which is attached to this programme. This creates flexibility for students who would like to continue their second year on the programme by either staying at KTH or deciding to do the second year abroad at one of the other EIT Digital member universities.
This is a two-year programme (120 ECTS credits) given in English. Graduates are awarded the degree of Master of Science, with a major in Electrical Engineering or Computer Science and Engineering. The programme is provided at KTH Campus by the School of Electrical Engineering and Computer Science (at KTH).
The courses in the programme cover topics such as marketing and market analysis, business formation, project work and management, and advanced ICT.
Year 1
Autonomous Systems Track
One of ME2062 and ME2094 shall be read.
Mandatory courses
- Introduction to Robotics (DD2410) 7.5 credits
- Machine Learning (DD2421) 7.5 credits
- Distributed Artificial Intelligence and Intelligent Agents (ID2209) 7.5 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- Entrepreneurship for Engineers (ME2072) 6 credits
- Business Development Lab of Entrepreneurship Engineers (ME2073) 9 credits
- Conditionally elective courses
- Technology-based Entrepreneurship (ME2062) 7.5 credits
- Internet Marketing (ME2094) 7.5 credits
Recommended courses
- Artificial Intelligence (DD2380) 6 credits
- Image Analysis and Computer Vision (DD2423) 7.5 credits
- Automatic Control, General Course (EL1010) 6 credits
- Analysis and Search of Visual Data (EQ2425) 7.5 credits
- Stochastic Simulation (II2206) 7.5 credits
- Deep Learning in Data Science (DD2424) 7.5 credits
- Hybrid and Embedded Control Systems (EL2450) 7.5 credits
- Control Theory and Practice, Advanced Course (EL2520) 7.5 credits
- Speech and Audio Processing (EQ2321) 7.5 credits
- Pattern Recognition and Machine Learning (EQ2341) 7.5 credits
- Embedded Systems (IL2206) 7.5 credits
Cloud and Network infrastructures Track
One of ME2062 and ME2094 shall be read.
Select either EP2200+EP2950 or ID2203+ID2211.
Mandatory courses
- Data-Intensive Computing (ID2221) 7.5 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- Advanced Internetworking (IK2215) 7.5 credits
- Entrepreneurship for Engineers (ME2072) 6 credits
- Business Development Lab of Entrepreneurship Engineers (ME2073) 9 credits
Conditionally elective courses
- Queuing Theory and Teletraffic Systems (EP2200) 7.5 credits
- Wireless Networks (EP2950) 7.5 credits
- Distributed Systems, Advanced Course (ID2203) 7.5 credits
- Data Mining, Basic Course (ID2211) 7.5 credits
- Technology-based Entrepreneurship (ME2062) 7.5 credits
- Internet Marketing (ME2094) 7.5 credits
Data Science Track
One of ME2062 and ME2094 shall be read.
Mandatory courses
- Machine Learning (DD2421) 7.5 credits
- Data Mining, Basic Course (ID2211) 7.5 credits
- Programming for Data Science (ID2214) 7.5 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- Entrepreneurship for Engineers (ME2072) 6 credits
- Business Development Lab of Entrepreneurship Engineers (ME2073) 9 credits
Conditionally elective courses
- Technology-based Entrepreneurship (ME2062) 7.5 credits
- Internet Marketing (ME2094) 7.5 credits
Recommended courses
- Visualisation (DD2257) 7.5 credits
- Artificial Intelligence (DD2380) 6 credits
- Image Analysis and Computer Vision (DD2423) 7.5 credits
- Machine Learning, Advanced Course (DD2434) 7.5 credits
- Statistical Methods in Applied Computer Science (DD2447) 6 credits
- Scalable Machine Learning and Deep Learning (ID2223) 7.5 credits
- Language Engineering (DD2417) 7.5 credits
- Deep Learning in Data Science (DD2424) 7.5 credits
- Artificial Neural Networks and Deep Architectures (DD2437) 7.5 credits
- Search Engines and Information Retrieval Systems (DD2477) 7.5 credits
- Distributed Systems, Advanced Course (ID2203) 7.5 credits
Human Computer Interaction and Design Track
One of ME2062 and ME2094 shall be read.
Mandatory courses
- Human-Computer Interaction, Introductory Course (DH1622) 7.5 credits
- Interaction Design Methods (DH2628) 7.5 credits
- Human-Computer Interaction, Research Seminars (DH2632) 3 credits
- Interaction Programming and the Dynamic Web (DH2642) 7.5 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- Entrepreneurship for Engineers (ME2072) 6 credits
- Business Development Lab of Entrepreneurship Engineers (ME2073) 9 credits
Conditionally elective courses
- Technology-based Entrepreneurship (ME2062) 7.5 credits
- Internet Marketing (ME2094) 7.5 credits
Recommended courses
- Machine Learning (DD2421) 7.5 credits
- Haptics, Tactile and Tangible Interaction (DH2670) 7.5 credits
- Evaluation Methods in Human-Computer Interaction (DH2408) 6 credits
- Distributed Artificial Intelligence and Intelligent Agents (ID2209) 7.5 credits
Visual Computing and Communication Track
One of ME2062 and ME2094 shall be read.
Mandatory courses
- Introduction to Visualisation and Computer Graphics (DH2320) 6 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- Entrepreneurship for Engineers (ME2072) 6 credits
- Business Development Lab of Entrepreneurship Engineers (ME2073) 9 credits
Conditionally elective courses
- Internet Marketing (ME2094) 7.5 credits
- Technology-based Entrepreneurship (ME2062) 7.5 credits
Recommended courses
- Visualisation (DD2257) 7.5 credits
- Machine Learning (DD2421) 7.5 credits
- Image Analysis and Computer Vision (DD2423) 7.5 credits
- Signal Theory (EQ1220) 7.5 credits
- Search Engines and Information Retrieval Systems (DD2477) 7.5 credits
- Computer Graphics and Interaction (DH2323) 6 credits
- Interaction Programming and the Dynamic Web (DH2642) 7.5 credits
- Speech and Audio Processing (EQ2321) 7.5 credits
- Pattern Recognition and Machine Learning (EQ2341) 7.5 credits
- Seminars in Information and Network Engineering (EQ2461) 3 credits
- Information Theory and Source Coding (EQ2845) 7.5 credits
Year 2
Autonomous Systems Track
Mandatory courses
- Degree Project in Computer Science and Engineering, specialising in ICT Innovation, Second Cycle (DA256X) 30 credits
- Degree Project in Electrical Engineering, specialising in ICT Innovation, Second Cycle (EA256X) 30 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- ICT Innovation Study Project (ME2096) 6 credits
Recommended courses
- Scalable Machine Learning and Deep Learning (ID2223) 7.5 credits
- Embedded Systems (IL2206) 7.5 credits
- Cyber-Physical Networking (EQ2871) 7.5 credits
- Applied Estimation (EL2320) 7.5 credits
- Modelling of Dynamical Systems (EL2820) 7.5 credits
- Artificial Intelligence (DD2380) 6 credits
Cloud and Network infrastructures Track
Mandatory courses
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- ICT Innovation Study Project (ME2096) 6 credits
- Degree Project in Computer Science and Engineering, specialising in ICT Innovation, Second Cycle (DA256X) 30 credits
- Degree Project in Electrical Engineering, specialising in ICT Innovation, Second Cycle (EA256X) 30 credits
Recommended courses
- Network Analytics (EP2420) 7.5 credits
- Networked Systems Security (EP2500) 7.5 credits
- Data Mining (ID2222) 7.5 credits
- Scalable Machine Learning and Deep Learning (ID2223) 7.5 credits
- Internet Security and Privacy (IK2206) 7.5 credits
- Seminars in Information and Network Engineering (EQ2461) 3 credits
Data Science Track
Mandatory courses
- Data-Intensive Computing (ID2221) 7.5 credits
- Data Mining (ID2222) 7.5 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- ICT Innovation Study Project (ME2096) 6 credits
- Degree Project in Computer Science and Engineering, specialising in ICT Innovation, Second Cycle (DA256X) 30 credits
Recommended courses
- Language Engineering (DD2417) 7.5 credits
- Deep Learning in Data Science (DD2424) 7.5 credits
- Artificial Neural Networks and Deep Architectures (DD2437) 7.5 credits
- Search Engines and Information Retrieval Systems (DD2477) 7.5 credits
- Distributed Systems, Advanced Course (ID2203) 7.5 credits
- Visualisation (DD2257) 7.5 credits
- Artificial Intelligence (DD2380) 6 credits
- Image Analysis and Computer Vision (DD2423) 7.5 credits
- Machine Learning, Advanced Course (DD2434) 7.5 credits
- Scalable Machine Learning and Deep Learning (ID2223) 7.5 credits
- Statistical Methods in Applied Computer Science (DD2447) 6 credits
Human Computer Interaction and Design Track
Mandatory courses
- Multimodal Interaction and Interfaces (DT2140) 7.5 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- ICT Innovation Study Project (ME2096) 6 credits
- Degree Project in Computer Science and Engineering, specialising in ICT Innovation, Second Cycle (DA256X) 30 credits
- Physical Interaction Design and Realisation (DH2400) 7.5 credits
Recommended courses
- Human-Computer Interaction, Research Seminars (DH2632) 3 credits
- Haptics, Tactile and Tangible Interaction (DH2670) 7.5 credits
- Developing Mobile Applications (ID2216) 7.5 credits
- Mobile Networks and Services (IK2560) 7.5 credits
Visual Computing and Communication Track
Mandatory courses
- Image and Video Processing (EQ2330) 7.5 credits
- Analysis and Search of Visual Data (EQ2425) 7.5 credits
- Research Methodology and Scientific Writing (II2202) 7.5 credits
- ICT Innovation Study Project (ME2096) 6 credits
- Degree Project in Electrical Engineering, specialising in ICT Innovation, Second Cycle (EA256X) 30 credits
- Degree Project in Computer Science and Engineering, specialising in ICT Innovation, Second Cycle (DA256X) 30 credits
Recommended courses
- Reinforcement Learning (EL2805) 7.5 credits
- Digital Signal Processing (EQ2300) 7.5 credits
- Digital Communications (EQ2310) 9 credits
- Machine Learning and Data Science (EQ2415) 7.5 credits
- Scalable Machine Learning and Deep Learning (ID2223) 7.5 credits
KTH Scholarships
KTH offers four different scholarship opportunities for master's studies. The KTH Scholarship covers the tuition fee of a one or two-year master’s programme. The KTH One-Year Scholarship is aimed at current KTH master's programme students and covers the tuition fee of the second year of studies. The KTH Joint Programme Scholarship is aimed at students in certain joint programmes and covers the tuition fee for the study period spent at KTH. The KTH India Scholarship is aimed specifically at students from India.
- KTH Scholarship
- KTH One-Year Scholarship
- KTH Joint Programme Scholarship
- KTH India Scholarship
Swedish Institute
SI Scholarship for Global Professionals
The SI Scholarship for Global Professionals covers the tuition fee for a master's programme and also includes living costs. It is open to students from 33 countries with previous work and leadership experience. You apply directly to SI after completing your application to KTH.
SI Scholarship Pioneering Women in STEM
The SI Scholarship Pioneering Women in STEM covers the tuition fee of a selection of master's programmes at KTH and also includes living costs. It is open to female students from Bangladesh, Indonesia, Kenya, Malaysia, Nigeria, the Philippines, Rwanda, South Africa, Thailand or Vietnam. You apply directly to SI after completing your application to KTH.
KTH associated scholarship organisations
KTH cooperates with the following organisations, providing scholarship opportunities for prospective KTH students.
- COLFUTURO (Programa Crédito Beca) for students from Colombia
- LPDP (Indonesia Endowment Fund for Education) for students from Indonesia
- FUNED for students from Mexico
- MESCYT for students from the Dominican Republic
- ANII for students from Uruguay
Scholarship portals
- IEFA database: The IEFA database offers a comprehensive scholarship search, grant listing, and international student loan programmes.
- Studyportals: The Studyportals scholarship database lists over 1,000 scholarships and grants for students worldwide applying for studies in the EU.
- Scholars4dev: Scholarships for Development is a database of scholarships open to students from developing countries.
- WeMakeScholars: WeMakeScholars helps students from India secure education loans from banks and NBFCs. They also list more than 26,000 international scholarships from different trusts, foundations, and the government. Bodies.
Deferment of student loans in the United States
KTH is an accredited institution at the US Department of Education and holds a Title IV 'Deferment Only' status (OPE ID 03274300). US students may defer payments on existing federal student loan accounts while enrolled in a master’s programme at KTH. The 'Deferment Only' status does not allow students to take out federal student loans for enrollment at KTH. However, the accreditation facilitates grant and loan opportunities for US students, as many private student loan institutions in the US use this designation as a requirement to grant new loans. Students who wish to defer payments must contact their lending institution in the US.
With the business-oriented focus combined with the technical specialisation, you will find a plethora of job and career opportunities. Examples include innovative start-ups, research-driven organisations and advanced IT businesses worldwide. The programme works closely with various top-tier companies to connect and prepare you for your future career. Throughout the programme, you will also interact with many of these businesses and industry partners, for example, by conducting your master’s degree project with them on real-life projects. In addition to improving students' cultural and language skills, this experience will give them expertise in their chosen technological field and excellent qualifications for managerial posts in global markets.