Mestrado in Matemática e Ciência de Dados in Europe

This master's program offers advanced training in data science, combining solid foundations in mathematics, statistics, and computer science with practical applications. In the first semester, students take core courses in mathematical modeling, statistical computing, big data programming, software engineering, and business intelligence. The second term builds on this foundation with modules such as machine learning, regression, data visualization, and data science workflows. Elective modules like deep learning or natural language processing allow students to tailor their studies.

In the third term, the focus shifts to advanced applications and ethical considerations, with courses in enterprise data science, urban technologies, business responsibility, and further specialization through electives such as learning from images or optimization. The final semester is dedicated to the master's thesis and oral examination. The curriculum is designed to prepare students for data-driven roles across various sectors, combining theoretical depth with real-world problem-solving.

This master's program is designed for students with a background in computer science, mathematics, or a closely related field, requiring a minimum of 180 ECTS. Applicants must demonstrate at least 20 ECTS in mathematics and statistics—including areas like analysis, linear algebra, numerical analysis, or probability—and at least 25 ECTS in computer science subjects such as programming, databases, or distributed systems. English proficiency at CEFR level B2 is also required.

The program provides comprehensive training in data science by integrating advanced coursework in machine learning, statistical computing, software engineering, data visualization, and applications in domains like enterprise and urban technologies. Elective modules cover areas such as natural language processing, deep learning, optimization, and sampling, allowing students to specialize in emerging fields. The final semester is dedicated to a master's thesis and an oral examination, emphasizing both academic rigor and practical relevance.

This master's program offers advanced training in economic theory and quantitative methods, with a strong focus on policy and data analysis. Students take courses in microeconomics, macroeconomics, econometrics, and optimization methods, while also exploring topics such as political economy, trade analysis, and competition policy. In the second year, they can specialize in areas like labor economics, behavioral economics, or data analysis of business systems. The program also includes applied components like machine learning in economics, skill development sessions, and culminates in a master's thesis.

To enroll in this master's program, candidates must hold a prior degree with at least 180 ECTS credits in fields such as economics, business, administrative sciences, mathematics, statistics, or related areas. Applicants from other fields may be admitted if they complete additional coursework of up to 60 ECTS credits, including subjects like microeconomics, macroeconomics, or international economics. These obligations can be met through prior studies or by taking specific exams before enrollment. In case of limited spots, selection is based on previous academic performance.

This master's program provides advanced training in Mathematics, offering two distinct tracks: the Research Option and the Professional Option. The Research Option prepares students for doctoral studies or academic careers through in-depth coursework in pure mathematics, logic, topology, number theory, and advanced algebra. The Professional Option focuses on applying mathematical methods to real-world problems, including courses in financial mathematics, numerical analysis, statistics, and optimization. Students take core and elective courses, choose a minor from areas like statistics or applied mathematics, and complete a master’s thesis. The curriculum includes topics such as algebraic geometry, quantum theory, cryptography, differential equations, and mathematical modeling.

This master's program welcomes applicants holding degrees in Mathematics or related disciplines obtained outside the Flemish Community, with each case evaluated individually. Students must demonstrate English proficiency through TOEFL, IELTS, or Cambridge exams unless they earned a prior degree entirely taught in English in Australia, English-speaking Canada, Ireland, New Zealand, the United Kingdom, or the United States, or possess a Belgian diploma. Applicants must also provide detailed course descriptions and grading information unless exempt through institutional partnerships or degrees from top 200 universities. The final admission decision is made by the Admissions Board based on the provided academic and language credentials.

This program focuses on advanced quantitative tools and economic theory to analyze complex economic issues and policies. It covers econometrics, macro- and microeconomics, game theory, monetary policy, time series analysis, and public sector economics. Students may choose specializations such as Financial Institutions and Markets or Economic Policy, and can also study abroad. Electives span topics like agent-based modeling, development economics, and ecological economics. Training in programming and statistical tools (MATLAB, R) is integrated. The program culminates in a research-based master’s thesis.

Applicants must hold a bachelor’s degree or equivalent, with at least 9 ECTS in mathematics and 6 ECTS in probability/statistics. English language proficiency is required (via TOEFL, IELTS, Cambridge, or PTE, taken within the last 2 years). Evaluation is based on a motivation letter (60%) and previous GPA (40%). The motivation letter includes a written essay (3,000–3,500 characters) discussing potential thesis topics and career goals, plus a 5-minute video CV outlining relevant experience and motivation. A minimum combined score of 66/100 is required for admission consideration. The committee may conduct follow-up interviews if needed.

This Master's program offers a highly flexible and specialized curriculum through a range of focused Areas of Expertise. Students can tailor their studies toward key fields such as Sustainability, Business and Data Analytics, International Development, Macroeconomics and Financial Markets, Public Policy, and Banking and Financial Regulation. Core training includes advanced micro- and macroeconomics, econometrics, and career development, while electives cover topics like machine learning, climate finance, health economics, blockchain, and political economy.

Applicants to the Master's programs must have completed their studies at an accredited or officially recognized institution in their home country. Since all academic activities are conducted in English, candidates must provide proof of English language proficiency at a B2 level or higher when applying. Portuguese is not required for life on campus. These programs are primarily designed for candidates with up to two years of professional experience, typically aged 23–24, though older applicants who align with the program's profile may also be considered.

This master’s program combines courses in data analysis, informatics, statistics, and social science to prepare students for analyzing complex societal phenomena. Core subjects include machine learning, data ethics, critical inquiry, and computational statistics. Students also explore topics like economic complexity, applied network science, and causal inference. The curriculum includes elective modules such as survey analytics, geography in data science, and big data applications. A two-part thesis consultation supports students in preparing their final research projects. This program is ideal for students seeking to bridge data science with the social scienc

Applicants must complete a two-part admission process: a written exam (Type A) worth 60 points, assessing language proficiency, quantitative analytical skills, and logical reasoning; and an oral interview worth 30 points, focusing on the applicant’s motivation and aptitude for the program.

This master’s program in business analytics allows students to choose one of three paths: Business Analyst, Data Engineer, or Information Analyst. The Business Analyst path focuses on data-driven decision-making, market analysis, customer behavior, and enterprise planning, preparing students for business development roles. The Data Engineer track emphasizes the management, mining, and processing of large data sets, with advanced courses in machine learning, big data, and AI applications. The Information Analyst specialization centers on information systems, user experience, digitalization, and research methods for organizational improvement. All tracks feature hands-on projects, teamwork, communication skills, and a research-based thesis, equipping graduates to address real-world challenges in business and industry.

For the specialization Business Analyst:
Applicants must have a bachelor’s degree in economics or business administration, or if from another field, at least 24 ECTS of relevant studies. The selection process is based on a preliminary video assignment (motivation, relevance of background, and communication skills) and the applicability and grades of prior studies. A minimum score is required, and a proof of English language proficiency must be submitted. Only complete applications with all required documents will be considered.

For the specialization Data Engineer:
Applicants must hold a bachelor’s degree in computer science, computer engineering, or a related field such as physics or applied mathematics, equivalent to at least three years of full-time studies. Very good or excellent grades in mathematics and subject-specific studies are required. Selection is based on the academic record and a letter of intent (statement of purpose, qualifications, work experience, and a proposed thesis topic). English proficiency must be proven, and all required documents must be submitted on time.

For the specialization Information Analyst:
Applicants need a bachelor’s degree suitable for studies in information processing science (minimum three years, 180 ECTS). Strong grades in subject-specific studies are required. Admission is based on cumulative GPA, the suitability and relevance of previous studies, and a detailed motivation letter (covering academic background, skills, work experience, program alignment, and thesis interests). English proficiency must be demonstrated with official test results, and all necessary documents must be attached to the application. Admission is competitive, and meeting the minimum criteria does not guarantee a place.

This master's program provides advanced training in both theoretical and applied statistics, with the option to specialize in tracks such as Biometrics, Social and Behavioral Sciences, Business, Industry, Theoretical Statistics and Data Science, or Official Statistics (EMOS). Students take core courses in probability, linear models, multivariate methods, statistical computing, and Bayesian analysis, followed by specialized modules tailored to their chosen track. Elective options and a master’s thesis allow further customization, encouraging students to focus on practical applications or methodological development. The program is ideal for those aiming to apply statistics across various sectors or pursue academic research.

Applicants to this master's program must hold an academic degree with at least two courses in introductory statistics. For students from outside Belgium, proof of English proficiency is required unless they earned a degree in Australia, English-speaking Canada, Ireland, New Zealand, the United Kingdom, or the United States. Accepted tests include TOEFL iBT (minimum 84), IELTS Academic (minimum 6.0 overall), and Cambridge Advanced or Proficiency (minimum 180). Additionally, students must provide English course descriptions and may be invited for an interview. A GRE General Test is recommended, especially if applicants come from universities not ranked in major international listings.

This master's program offers a comprehensive education in mathematics with a focus on both theoretical and applied areas. Students follow a flexible curriculum that includes core subjects in functional analysis, topology, algebra, and differential equations, while also choosing from a wide range of advanced courses such as cryptology, numerical methods, algebraic geometry, financial mathematics, and stochastic modeling. The program allows for deep specialization through state exam blocks and extensive elective options, culminating in a diploma thesis and oral state examination in mathematics.

To apply for this master's program, students must submit a legalized copy of their bachelor's degree diploma (or confirmation of ongoing studies), an official transcript of completed courses, a structured CV, a copy of their passport, two academic reference letters, a motivation letter, and a recognized English language certificate. All documents must be in English and confirm the applicant's academic qualifications and language proficiency.

This master's program offers two specialization tracks: Mathematics Education and Mathematics. The Mathematics Education track emphasizes teaching strategies, digital tools in math instruction, and theoretical perspectives, with a strong focus on developing effective teaching methods. The Mathematics track is research-oriented, featuring advanced courses such as topology, measure theory, functional analysis, stochastic processes, and stochastic differential equations. Students also take research methodology and elective subjects tailored to their interests. Depending on the year, specific advanced mathematics courses alternate (e.g., numerical linear algebra and stochastic processes in odd years). Both tracks culminate in a comprehensive master’s thesis, and mathematics education students can customize electives based on their teaching goals.

To be eligible for this master's program, applicants must have a bachelor's degree or equivalent education lasting at least three years (180 ECTS), including a minimum of 80 ECTS in mathematics or closely related subjects. At least 20 ECTS of the coursework must be at an advanced level. A minimum overall grade of C or equivalent is required for admission. English proficiency must be demonstrated through tests such as IELTS (minimum 6.0), TOEFL (minimum 80 iBT), PTE Academic (minimum 62), or Cambridge exams (B2 First with "A", C1 Advanced, or C2 Proficiency), or through other accepted qualifications.

This master’s program focuses on equipping students with advanced analytical, technological, and managerial skills. It offers two specializations: Innovation and Digital Management and Analytics for Business. Core subjects include data visualization, innovation policy, econometrics, programming, and business growth strategies. One track emphasizes digital business analysis, covering areas like process management, requirements engineering, and data analytics. The other centers on innovation management, including CRM, intrapreneurship, HR, and supply chains. The program concludes with a research-based master's thesis aligned with the chosen specialization.

Applicants must hold a bachelor’s degree (or equivalent) in economics, mathematical sciences, or technology sciences (including IT), to be obtained by the end of July. English language proficiency is mandatory and must be proven with accepted tests like TOEFL iBT, IELTS Academic, Cambridge English, or PTE Academic—taken no more than two years before applying. Applications are assessed based on a motivation letter (60%) and the average grade from prior studies (40%). A minimum combined score of 66 out of 100 is required for admission consideration.

The program is structured into five modules. The Preparatory Module (27 ECTS) includes core statistical and mathematical courses such as Generalized Linear Models, Statistical Machine Learning, and Time Series Analysis. The Speciality Module (27 ECTS) focuses on actuarial and financial topics like Life and Non-Life Insurance Mathematics, Computational Finance, and Risk Theory. The Elective Module (30 ECTS) offers advanced actuarial, economic, and computer science courses, along with practical training. Students may also take Optional Courses (6 ECTS) and participate in Study Abroad programs (6–15 ECTS). The curriculum concludes with a Master’s Thesis (30 ECTS).

Applicants must hold a bachelor’s degree with at least 24 ECTS in mathematics (including calculus, probability, statistics) and 6 ECTS in computer science. Admission is based on the previous study grade (40%), a motivation letter (30%), and an interview (30%). The motivation letter should explain goals, background, and specific interests in actuarial and financial engineering. The interview assesses field knowledge, motivation, problem-solving, and communication. English proficiency (B2 level) is mandatory, demonstrated by accepted international language tests.