Course Structure

Learning takes place through a combination of face-to-face teaching and independent study, including lectures, practical tutorials, laboratory sessions, personal development sessions, real-life project briefs and case studies.

Students study 60 ECTS credits per year. The structure of the course is a subject to change by feedback received from a variety of sources.

Entry requirements

1. High school/Lyceum/College diploma or higher

2. Proof of English Language Proficiency:

•  - TOEFL iBT 46 or higher
• Note: We accept only the TOEFL iBT taken at approved test centers. We do not accept the TOEFL iBT Home Edition.
•  - IELTS 5.5 or higher
•  - CEFR B2
•  - Exemptions (with a minimum pass mark) from the TOEFL, IELTS or CEFR are given for students who have one of the following equivalents:

Note: If your English proficiency test certificate is not yet available, please upload it via your personal account no later than August 18, 2025.

Entrance Exam

• - Math & Logical Thinking
• - Exemptions from the Math & Logical Thinking are given for students who have one of the following equivalents:

Please use the online equivalency calculator above to see the equivalency of your score to Math & Logical Thinking exam scores.

You can also check the equivalent of your score to the Math & Logical Thinking entrance exam scores using the table below.

Graduation Requirements

Students will be allowed to graduate upon completion of all requirements listed below:

• - Students must have a minimum 2.00 GPA/CGPA at the end of their final semester;
• - Student must have a minimum of 240 ECTS or as designated in Handbook;
• - Students must successfully complete all University and Program requirements;
• - Students cannot have any outstanding Incompletes or IP grades on their transcripts;
• - Student must complete all degree requirements within 7 (seven) years including any leave periods, of the initial program registration date.

Fees and funding:

Career / Job opportunities

Economics and Data science is a dynamic and continually evolving field. The vast knowledge and many skills related to economics and data science mean that professionals in this field have a variety of job options and can work in a range of industries, such as economics, finance, accounting, health care, technology, marketing or others. Professionals can have an array of choices when it comes to finding a job that fits their interests and abilities. You might start out as:

Economist - An economist is a professional and practitioner in the social science discipline of economics. The individual may also study, develop, and apply theories and concepts from economics and write about economic policy.

Financial analyst - A financial analyst is a professional, undertaking financial analysis for external or internal clients as a core feature of the job. The role may specifically be titled securities analyst, research analyst, equity analyst, investment analyst, or ratings analyst.

Statistician - A statistician is a person who works with theoretical or applied statistics. The profession exists in both the private and public sectors. It is common to combine statistical knowledge with expertise in other subjects, and statisticians may work as employees or as statistical consultants

Actuary - An actuary is a business professional who deals with the measurement and management of risk and uncertainty. The name of the corresponding field is actuarial science. These risks can affect both sides of the balance sheet and require asset management, liability management, and valuation skills.

Data scientist - A data scientist determines the most effective ways of collecting or evaluating data sets. Data scientists use analytical abilities to assess data and discover insights that can help businesses make strategic improvements. An economics and data science degree can help data scientists evaluate the causal relationships between data points or sets in different ways.

Data engineer - Data engineers build the infrastructure, software tools and applications that gather and analyze sets of data. Their responsibilities include transforming unstructured data into useable formats, finding patterns within data sets and setting batch processing systems in motion. With an economics background, data engineers may have unique insights into data trends and structures.