Machine Learning, Data Science and Artificial Intelligence, Master of Science (Technology)
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Description
What exactly is intelligence, and how does it evolve? What is learning and why has 'learning to learn' become a crucial skill in today’s world? Wanting to find answers to questions as plain and straightforward as these can be enough of a reason for someone to study machine learning, data science and artificial intelligence. Yet, these fields also deal with some of the most challenging problems of the 21st century. This makes the Machine Learning, Data Science and Artificial Intelligence (or "Macadamia") major at Aalto University an ideal study environment for talented students who look for a challenging study option and are motivated to get out of their comfort zone. Whether finding new solutions to tackle climate change or to better understand the causes of epidemics, artificial intelligence, data science and machine learning play a role.
A Macadamia graduate:
- is able to formalize data-intensive problems in data science and artificial intelligence in terms of the underlying statistical and computational principles.
- is able to select and apply a suitable machine learning method to solve aproblem in industry or academia and apply the methods to the problem.
- can interpret the results of a machine learning method, assess their credibility, and communicate the results to experts from different fields.
- can implement state-of-the-art machine learning methods, and design and implement novel methods by modifying existing approaches.
- understands the theoretical foundations of the machine learning field to the extent of being able to follow research in the field.
- is familiar with ethical principles and techniques intended to inform the development and responsible use of artificial intelligence.
Tuition fees and scholarships
The tuition fee for this programme is 17 000 euros per academic year. Citizens of European Union (EU), the European Economic Area (EEA) or Switzerland do not pay tuition fees. Citizens of other countries must pay tuition fees.
Aalto University offers a small number of scholarships in the form of tuition fee waivers to fee-paying students. Scholarships can be awarded to the highest-achieving applicants based on the programme's evaluation criteria. Applicants are ranked according to the criteria outlined on the programme's webpage.
More information on tuition fees and scholarships at Aalto University is available at the Scholarships and Tuition Fees webpage.
Structure of studies
Master’s Programme in Computer, Communication and Information Sciences – major Machine Learning, Data Science and Artificial Intelligence comprises a total of 120 ECTS credits.
The two-year programme consists of:
- Major studies (60 ECTS)
- Elective studies (30 ECTS)
- Master’s thesis (30 ECTS)
Our curricula are designed for full-time students. While master's students often work part-time during academic terms or full-time in the summer, full-time work during academic terms is discouraged. Part-time work requires careful planning and extra effort, as not most courses are available online or every year.
While there may be courses that are available online, as a general guideline, studies at Aalto University School of Science require on-campus attendance.
Specialisations
Aalto University’s Department of Computer Science is quickly rising in rankings and is now among the top departments in Europe. Students in the Machine Learning, Data Science and Artificial Intelligence major are provided with access to cutting edge research and guidance from leaders in the field.
The studies emphasise active, hands-on learning. Projects and different practical assignments are meant to engage students in active learning and encourage them to try out things by themselves instead of remaining passive recipients of information. The faculty consists of enthusiastic and internationally acclaimed professors and researchers in the field, all contributing to an enjoyable and encouraging learning environment. To give concrete examples of the courses available, the following is a selection from the programme’s extensive curriculum:
- Deep Generative Models (5 ECTS)
- Bayesian Data Analysis (5 ECTS)
- Probabilistic Machine Learning (5 ECTS)
- Artificial Intelligence (5 ECTS)
- Federated Learning (5 ECTS)
- Quantum Machine Learning (5 ECTS)
- Computer Vision (5 ECTS)
Major compulsory courses at the beginning of the studies provide a strong foundation before further study in specific sub-areas. Students have the opportunity to dive deeper into areas such as Digital Health, Speech and Language, or Large-Scale Computing. There is also a range of general optional courses for students to choose from and it is possible to include optional courses from other majors in the study plan by agreement with the professor in charge of the major.
More information on the programme content and curriculum can be found in the Student guide. There may be some changes to the courses for the academic years 2026–2028 — the new curricula will be published in April 2026, when they will also be visible in the Student guide.
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Internationalisation
The study environment in the programme is strongly international and studies are conducted in multicultural groups. The School of Science offers diverse possibilities for student exchange and internships all over the world. Students may find themselves doing an internship in Silicon Valley or taking a summer course at one of Aalto's partner institutions.
Machine Learning, Data Science and Artificial Intelligence students have also the opportunity to take their second-year studies at EURECOM, France, or Grenoble INP, France and complete a double degree graduating from both Aalto University and EURECOM or Grenoble INP. In addition, the Macadamia major co-operates closely with ELLIS, the European Laboratory for Learning and Intelligent Systems, which has some of the best academic institutions and scientists under its umbrella. Should the students want to become top researchers in the field, they have an excellent opportunity for that.
Aalto University is international by nature, welcoming thousands of degree and exchange students from abroad every year. These students join the diverse Aalto community not only through their studies, but also through multiple free time events, celebrations and extracurricular activities around the campus. Active tutoring programs and support services work hard to help international students integrate to the Nordic culture and feel at home in Finland.
Further study opportunities
The degree programme provides eligibility for scientific postgraduate studies in Finland. The skills learned in the programme create an excellent basis for doctoral studies at Aalto University, another Finnish university or top international universities. Doctoral graduates from Aalto University continue to researcher or other academic career or high-level business positions, among other things. Read more about applying for doctoral studies at Aalto University: https://www.aalto.fi/en/doctoral-education/how-to-apply-for-doctoral-studies
Career opportunities
Machine learning and artificial intelligence are disrupting virtually every business in every industry. Staying on top of this revolutionary technology is imperative for organisations seeking to maintain a competitive edge.
Since the demand for AI professionals outpaces the current availability of skilled AI engineers, the graduates of this major have limitless opportunities open for them, ranging from process industry to data science. Recent spearhead application areas include biology, medicine, astrophysics, interactive technologies, information retrieval, information visualisation, neuroinformatics, and social-network analysis.
Typical entry-level job titles of recent graduates include
- Analyst, Analytics Engineer
- Data Analyst, Data Scientist
- DevOps Engineer
- Machine Learning Engineer
- Software Developer
- Software Engineer
Graduates can expect to advance rapidly in their chosen career.
Examples of companies our recently graduated alumni work for: Accenture, Aureus Analytics, Discover Financial Services, Futurice, Elsevier, Jongla, Nokia, Omniata Inc, Reaktor, Sanoma, Silo AI and Verto Analytics.
Our recently graduated alumni are PhD students in the following universities: Aalto University, Brown University, Carnegie Mellon University, French Institute for Research in Computer Science and Automation (Inria), Purdue University, Télécom Paris Tech, University of Bristol, University of California - Santa Cruz, University of Iowa, University of Surrey.
Aalto University has well-established career services to support students’ employment in Finland and abroad. Thanks to the flexible curriculum, many Aalto students work already during their studies and guarantee themselves entry positions before graduation. There is also a very active entrepreneurship community at Aalto, working as a springboard for founding a company.
School of Science graduates in working life
Graduates from the School of Science at Aalto University have very good employment prospects in positions corresponding to their education. On this page, you can find information about employment and career development five years after graduation.
Research focus
The studies in the programme are closely related to the world-class research conducted at the Department of Computer Science. The best students from this major are warmly welcome as doctoral students in Aalto University’s research groups.
Co-operation with other parties
There is close collaboration in teaching and research between Aalto University and the University of Helsinki in the form of joint activities within the Finnish Center for Artificial Intelligence (FCAI). The latter brings together top talents in academia, industry and public sector to solve real-life problems using both existing and novel AI. One of the current research areas centres around the opportunities that AI creates for medicine. Excellent students from this major can continue their studies in the Helsinki Doctoral Education Network in Information and Communication Technology (HICT).
Students can also include multidisciplinary studies in their degree by studying a minor or optional courses from other fields.
Aalto University is well-known for bridging disciplines of business, arts, technology and science. The lively campus and freedom of choosing elective courses across the University bring students from different fields under one roof. This spontaneous multidisciplinary environment sparks new ideas, gathers enthusiasts around them and gives birth to friendships, networks, and every so often, startups.
Study-option-specific evaluation criteria
Applicants to Machine Learning, Data Science and Artificial Intelligence (Macadamia) meeting the general eligibility criteria for master's studies are evaluated according to the below Evaluation criteria based on their admission group. The evaluation process is described under Evaluation process. In addition to the obligatory application documents, this study option asks the applicants to submit also the documents listed under Requested documents.
Admission groups
- Admission group 1: Bachelor’s degree from a higher education institution in the European Union (EU) or the European Economic Area (EEA) member states or Switzerland.
- Admission group 2: Bachelor’s degree from a higher education institution in a non-EU/EEA country
The degree that gives the applicant the eligibility to apply (i.e., bachelor's degree) determines which admission group the applicant belongs to even in cases where the applicant has more than one higher education degree.
Admission group 1
Bachelor’s degree from a higher education institution in an EU/EEA country or Switzerland
Macadamia applications in Admission group 1 are evaluated based on the following criteria:
Academic performance
The programme is looking for applicants with excellent academic performance in their previous studies. In study options where the number and quality of applications is high, this means that the applicant has achieved consistently excellent grades throughout the degree studies (very high weighted average grade or GPA).
The applicant’s prior academic performance will be evaluated based on the grade point average (GPA) and grades in key courses. The time spent on the previous studies will also be considered. All the applicant’s previous university studies, including incomplete degrees and non‐degree studies, will be taken into consideration when evaluating academic performance.
Applicants from Finnish universities of applied sciences (AMK)
The minimum GPA for applicants from Finnish universities of applied sciences is 4.0. Meeting the minimum GPA does not guarantee admission to the programme. Applicants with GPA below the limit cannot be admitted. Programme’s courses or equivalent courses completed in the open university or as non-degree studies with excellent grades may support the application.
International applicants
For applicants whose degree is completed abroad (i.e., not in Finland), the interpretation of excellent academic performance depends on the applicant's country and recognition and quality of university.
Relevance of previous studies
Applicants are expected to have a high-quality Bachelor’s degree in computer science, software engineering, communications engineering, or electrical engineering. Excellent candidates with degrees in other fields including but not limited to information systems, engineering, natural sciences, mathematics or physics will be considered if they have sufficient studies in the required areas.
The required university-level studies for Macadamia applicants are:
- mathematics (linear algebra, calculus, probability theory, statistics, and discrete mathematics)
- computer science (good programming skills, data structures and algorithms, databases)
Studies in at least some of the following subjects are considered an advantage:
- additional knowledge of mathematical methods (important)
- optimization, stochastic methods, advanced probability theory or advanced statistics
- artificial intelligence, machine learning or data mining
- computational modelling or data analysis
- big data applications or signal processing
- theory of computation, computer networks or software engineering
The contents of applicant’s previous studies are evaluated based on the courses on the official transcript of records.
Recognition and quality of institution
Suitability
The applicant should be motivated to study the chosen subject and committed to full-time studies with a plan to complete the Master’s degree in two years. We are looking for applicants who are able to express clearly the reasons for applying to the study option and describe why they would be excellent candidates for it.
Studies in the Master’s programme should provide genuinely new knowledge for the applicant. If the applicant already has a Master’s or higher degree or is studying towards one, the motivation letter should clearly indicate why another one is necessary. In most cases, non-degree studies are recommended instead.
Other areas of competence
Beyond their academic record, applicants may have other experience, knowledge and qualifications that prepare them for the Master’s studies and distinguish them among their peers.
We particularly value demanding work experience in the area of the planned studies, participation in scientific research leading to publications, entrepreneurship, and special achievements such
as success in competitions (e.g. Junction Hackathon).
This is the master version of the CCIS programme-specific evaluation criteria, and its Finnish and
Swedish versions are its translations.
During the evaluation of eligible applications, Macadamia applications in Admission group 1 are first evaluated based on the following criteria:
- Academic performance
- Relevance of previous studies
Only the applications which fulfil the requirements for these criteria will be evaluated against the full set of evaluation criteria. It is not possible to compensate for these criteria with other criteria. This means, for example, that motivation for Master level studies in this subject does not compensate for low grades or that relevant work experience does not compensate for higher education studies in the required subjects.
After the evaluation of the remaining criteria below, the best applicants will be selected based on the joint evaluation of all criteria.
- Recognition and quality of institution
- Suitability
- Other areas of competence
The admission process is very competitive and only the best applicants are selected yearly. Not all applicants fulfilling the requirements can be admitted.
Applications missing any of the required study-option specific documents i.e. motivation letter, curriculum vitae (CV) form are rejected, and not evaluated against any of the evaluation criteria.
In addition to obligatory application documents, the Macadamia applicants in Admission group 1 are requested to provide the following study-option-specific documents:
- Motivation letter*
- Based on your application documents (transcript of records, CV, other supporting documents), reflect on your
- relevant experience and achievements,
- expectations and motivation for MSc studies majoring in Machine Learning, Data Science and Artificial Intelligence at Aalto University, and
- future career aspirations and how MSc studies in Machine Learning, Data Science and Artificial Intelligence contribute to them.
- The motivation letter should be written in English. The recommended length is one page (font size 11 pt).
- Based on your application documents (transcript of records, CV, other supporting documents), reflect on your
- Curriculum Vitae (CV)*
*) The lack of this document will cause rejection.
In addition, these additional documents add value to your application:
- At least one original recommendation letter
- The recommendation letter should preferably be from a university professor, lecturer or a thesis instructor who has supervised the applicant’s studies. There are no specific instructions for the contents of the recommendation letter. The letter should comment on the applicant’s suitability and aptitude for the programme. Recommendation letters written by work supervisors are accepted as well in case some time has passed since graduation.
- Short course descriptions of courses taken in the relevant subject areas
- Work certificates and other certificates of relevant achievements
- Copies of any scientific publications
- Official transcript of records for other university studies which are not included in the mandatory part of the application (e.g. incomplete degrees, exchange studies, non‐degree studies)
Admission group 2
Bachelor’s degree from a higher education institution in a non-EU/EEA country
Macadamia applications in Admission group 2 are evaluated based on the following criteria:
Standardized tests
Academic performance
The programme is looking for applicants with excellent academic performance in their previous studies. In study options where the number and quality of applications is high, this means that the applicant has achieved consistently excellent grades throughout the degree studies (very high weighted average grade or GPA).
The applicant’s prior academic performance will be evaluated based on the grade point average (GPA) and grades in key courses. The time spent on the previous studies will also be considered. All the applicant’s previous university studies, including incomplete degrees and non‐degree studies, will be taken into consideration when evaluating academic performance.
International applicants
For applicants whose degree is completed abroad (i.e. not in Finland), the interpretation of excellent academic performance depends on the applicant's country and recognition and quality of university. In the previous years, at least the following GPAs have been required: Bangladesh 3.70/4, China (Mainland) 3.50/4 or 85/100, India 8.0/10 or 75%, Pakistan 3.60/4. Meeting these GPA requirements does not guarantee admission to the programme.
Relevance of previous studies
Applicants are expected to have a high-quality Bachelor’s degree in computer science, software engineering, communications engineering, or electrical engineering. Excellent candidates with degrees in other fields including but not limited to information systems, engineering, natural sciences, mathematics or physics will be considered if they have sufficient studies in the required areas.
The required university-level studies for Macadamia applicants are:
- mathematics (linear algebra, calculus, probability theory, statistics, and discrete mathematics)
- computer science (good programming skills, data structures and algorithms, databases)
Studies in at least some of the following subjects are considered an advantage:
- additional knowledge of mathematical methods (important)
- optimization, stochastic methods, advanced probability theory or advanced statistics
- artificial intelligence, machine learning or data mining
- computational modelling or data analysis
- big data applications or signal processing
- theory of computation, computer networks or software engineering
The contents of applicant’s previous studies are evaluated based on the courses on the official transcript of records.
Recognition and quality of institution
Suitability
The applicant should be motivated to study the chosen subject and committed to full-time studies with a plan to complete the Master’s degree in two years. We are looking for applicants who are able to express clearly the reasons for applying to the study option and describe why they would be excellent candidates for it.
Studies in the Master’s programme should provide genuinely new knowledge for the applicant. If the applicant already has a Master’s or higher degree or is studying towards one, the motivation letter should clearly indicate why another one is necessary. In most cases, non-degree studies are recommended instead.
Other areas of competence
Beyond their academic record, applicants may have other experience, knowledge and qualifications that prepare them for the Master’s studies and distinguish them among their peers.
We particularly value demanding work experience in the area of the planned studies, participation in scientific research leading to publications, entrepreneurship, and special achievements such
as success in competitions (e.g. Junction Hackathon).
This is the master version of the CCIS programme-specific evaluation criteria, and its Finnish and
Swedish versions are its translations.
During the evaluation of eligible applications, Macadamia applications in Admission group 2 are first evaluated based on the following criteria:
- Standardized tests
- Academic performance
- Relevance of previous studies
Only the applications which fulfil the requirements for these criteria will be evaluated against the full set of evaluation criteria. It is not possible to compensate for these criteria with other criteria. This means, for example, that motivation for Master level studies in this subject does not compensate for low grades or that relevant work experience does not compensate for higher education studies in the required subjects.
After the evaluation of the remaining criteria below, the best applicants will be selected based on the joint evaluation of all criteria.
- Recognition and quality of institution
- Suitability
- Other areas of competence
The admission process is very competitive and only the best applicants are selected yearly. Not all applicants fulfilling the requirements can be admitted.
Applications missing any of the required study-option specific documents, i.e. Graduate Records Examination (GRE) test result, motivation letter, curriculum vitae (CV), are rejected, and not evaluated against any of the evaluation criteria.
Graduate Records Examination (GRE) test result is obligatory for Macadamia applicants in Admission group 2.
- The accepted exams are the GRE General Test and GRE Revised General Test. At home tests are accepted. The GRE Subject Test is not acceptable. See the homepage of GRE for more information.
- The official test scores must arrive at Aalto University directly from the testing organisation by 9 January 2026. The GRE test reporting code for Aalto University is 7364.
- GRE scores are valid for five years after the test day. For 2026 admissions, the oldest acceptable test date is 1 December 2020.
In addition to obligatory application documents, the Macadamia applicants are also requested to provide the following study-option-specific documents:
- Motivation letter*
- Based on your application documents (transcript of records, CV, other supporting documents), reflect on your
- relevant experience and achievements,
- expectations and motivation for MSc studies majoring in Machine Learning, Data Science and Artificial Intelligence at Aalto University, and
- future career aspirations and how MSc studies in Machine Learning, Data Science and Artificial Intelligence contribute to them.
- The motivation letter should be written in English. The recommended length is one page (font size 11 pt).
- Based on your application documents (transcript of records, CV, other supporting documents), reflect on your
- Curriculum Vitae (CV)*
*) The lack of this document will cause rejection.
In addition, these additional documents add value to your application:
- At least one original recommendation letter
- The recommendation letter should preferably be from a university professor, lecturer or a thesis instructor who has supervised the applicant’s studies. There are no specific instructions for the contents of the recommendation letter. The letter should comment on the applicant’s suitability and aptitude for the programme. Recommendation letters written by work supervisors are accepted as well in case some time has passed since graduation.
- Short course descriptions of courses taken in the relevant subject areas
- Work certificates and other certificates of relevant achievements
- Copies of any scientific publications
- Official transcript of records for other university studies which are not included in the mandatory part of the application (e.g. incomplete degrees, exchange studies, non‐degree studies)
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Contact information
Learning Services at Aalto University School of Science
For enquiries regarding the programme-specific application documents or studies in the programme, please contact Learning Services of Aalto University School of Science
masters-sci@aalto.fi
Admission Services
For enquiries regarding the application process, obligatory application documents or English language proficiency, please contact Admission Services
admissions@aalto.fi