Oldenburg MSc Applied Economics and Data Science

What is University of Oldenburg MSc Applied Economics and Data Science?

Oldenburg’s MSc Applied Economics and Data Science is a 2 years, 120 ECTS programme. It brings economics and empirical methods together with data science methods before independent final work. The full planning total is INR 28.61 lakh. For an Indian applicant, the first decision is whether the sequence matches prior study and intended work.

The official description confirms an on-campus academic sequence with taught study, choice and independent assessment. That balance defines this programme more clearly than its award label alone. The examination regulation controls credit recognition, module order and the final award.

How much does MSc Applied Economics and Data Science at the University of Oldenburg cost?

For planning, use EUR 25,832 plus INR 26,400, or about INR 28.61 lakh, across 24 months. The total uses the published programme fee, current semester contribution, the university's EUR 1,000 monthly living estimate, APS and the adult national visa fee.

The first-year blocked-account amount remains the student's living money. It is not added again above the full living plan. Converted at EUR 1 = INR 109.7500 using the European Central Bank reference rate for 3 September 2026. Flights, deposits, translations, uni-assist fees and bank spreads are excluded.

Proof of sufficient funds is required for the student visa.German Missions in India study visa funding rule

The Oldenburg semester contribution, fee schedule and ECB reference file support the calculation.

The current programme fee is EUR 0. Standard Oldenburg degree programmes have no tuition, but the published fee schedule names separate charges for three programmes in this cluster. The exact enrolment and programme invoice control the amount due.

The university publishes a EUR 1,000 monthly living estimate. This plan covers 24 months. Rent deposits, travel and personal spending can still move the cash requirement above it.

The Winter 2026/27 semester contribution is EUR 457.90. A later semester can change this charge, so the table is a planning base rather than a fee guarantee.

Rupee totals change with exchange rates even when euro charges do not. Part-time earnings are excluded because a job, work schedule and income are not guaranteed.

Can an Indian applicant enter University of Oldenburg MSc Applied Economics and Data Science?

An Indian application is credible when the transcript clearly proves economics, maths, statistics and econometrics credits. Oldenburg evaluates degree content, accepted language evidence and programme documents separately. APS and detailed module descriptions help the admissions team interpret the qualification, but they don't replace a missing academic prerequisite.

The official admission page for MSc Applied Economics and Data Science gives the binding subject screen. A previous degree programme is ordinarily suited to the subject if it has taught the following competences in the areas: English Language Proficiency see admissions regulations For more details see Foreign language skills on this page. Bachelor’s degree or equivalent qualification from prior studies in Sustainability Economics, Economics, Business Administration, Economics and Business Administration, Business Informatics or in a closely related field worth at least 180 ECTS credits. Economics with at least 20 ECTS credits Mathematics with at least 10 ECTS credits Statistics with at least 10 ECTS credits Econometrics with at least 5 ECTS credits Level B2 of Common European Framework of Reference for Languages (CEFR)

For this programme, the practical comparison is between completed modules and economics and empirical methods. A degree name on its own doesn’t establish that match, particularly when an adjacent discipline contains little of the named preparation.

An Indian file should keep original credits, grades and module descriptions visible. APS verifies the academic record, while the University of Oldenburg still makes its own admission decision for MSc Applied Economics and Data Science.

How should an Indian student apply for Oldenburg MSc Applied Economics and Data Science?

The selected intake is Winter 2027/28, with 15 Jun 2027 as the published planning deadline for this route. Indian degree holders normally apply through uni-assist and include APS evidence, unless the programme names a separate application channel. Start the document sequence well before the closing date.

Subject fit, APS, uni-assist or the named programme route, admission decision, then student visa

The allowances are Nbyula planning estimates, not processing times published by University of Oldenburg.

The exact programme application page controls the route. Applicants with an international degree use the course-specific Oldenburg route and normally submit through uni-assist. Indian qualifications require APS evidence.

The checked source supports The published planning deadline is 15 June 2027 for the selected winter route. Deadline treatment can differ by nationality, degree origin and entry semester, so do not substitute another Oldenburg programme’s date.

The complete file normally includes academic records, grading information, language evidence, identity documents and translations where applicable. Early submission leaves time for a document defect without changing the deadline.

Admission and the student visa are separate decisions. An offer does not guarantee a visa, housing or arrival before enrolment.

What jobs can follow University of Oldenburg MSc Applied Economics and Data Science?

The published curriculum most directly supports work as economic data analyst, policy analyst or doctoral researcher. These are study-linked directions, not placement promises. Oldenburg doesn't publish an audited placement rate or salary distribution for this exact programme, so prior experience and competitive recruitment remain material.

For MSc Applied Economics and Data Science, the university publishes no exact placement rate or salary distribution for this programme. The legal job-search period is time to seek suitable work, not an employment promise.

The programme career description connects the course with these fields. Graduates of this degree programme are particularly suited for the following careers: All of these employers are involved in the design or implementation of policy instruments, such as a carbon tax, and therefore must assess the impact and potential consequences of their introduction. All of these companies are confronted with government regulations in their markets that may affect profits, development opportunities and investment decisions. As such, they need to make predictions about the impact of regulations in order to be able to make decisions. Since this degree programme is research-oriented, graduates may also pursue a doctorate. Decision-makers in politics and administration who are responsible for designing and implementing policy measures. Examples of potential employers include: The Federal Ministry for the Environment, Nature Conservation and Nuclear Safety The Federal Ministry of Economics and Energy The Lower Saxony Ministry for the Environment, Energy, Construction and Climate Protection Corresponding state ministries in other federal states Corresponding institutions at EU level The German Environment Agency NGOs such as BUND, WWF Political parties Professionals in the private sector who are responsible for assessing the impact of government regulations and evaluating their consequences. Examples of potential employers include: Automotive companies Energy suppliers IT companies Employees at universities and research institutions who conduct research on the implementation and efficiency of regulations and government measures. Examples of potential employers include: Economic research institutes, such as the German Institute for Economic Research (DIW), the Centre for European Economic Research (ZEW), the Institute for the World Economy (IfW) or Institute for Economic Research (IfO Institute) Universities that specialise in relevant research areas. In the field of sustainability: University of Oldenburg, University of Hamburg, University of Lüneburg, etc.

The route from economics and empirical methods to master’s thesis explains why economic data analyst is a defensible direction. It doesn’t show that every graduate receives that title, enters the same sector or earns the same salary.

After successful study, Germany’s Residence Act section 20 can permit up to 18 months for a qualifying job search when the graduate has sufficient funds. That period isn’t an employment, sponsorship or permanent-residence guarantee.

Who is University of Oldenburg MSc Applied Economics and Data Science for?

The strongest fit is a graduate whose prior study supports economics and empirical methods and whose intended work connects with economic data analyst. An adjacent-field applicant needs a written module-level ruling. A candidate missing the stated preparation should resolve that gap before paying for verification, application or relocation.

A strong shortlist starts with the academic sequence from economics and empirical methods to data science methods. That sequence suits someone who wants to use the master’s for economic data analyst rather than only collect a broad award title.

An adjacent record needs a faculty ruling because Oldenburg assesses subject content. The application is stronger when every relevant module shows its original credit value, assessment and syllabus rather than relying on a self-created equivalence.

Someone whose goal sits outside economic data analyst, policy analyst, doctoral researcher should compare a different syllabus. The programme’s value depends on wanting its actual academic route, not merely the University of Oldenburg name.

What does the University of Oldenburg MSc Applied Economics and Data Science curriculum contain?

The current published 120 ECTS curriculum is organised around Economics and empirical methods, Data science methods, Specialisation and research, Master's thesis. Current regulations control sequencing and availability. Read the credit pattern as the course's academic balance before choosing a specialisation route, while the current regulations control sequencing and availability.

The note “Published curriculum area” applies to 4 components in this table.

• Complete the approved 120 ECTS programme
• Follow the examination regulations for compulsory and elective credits
• Module availability and sequencing can vary by semester

The published credit groups give MSc a distinct academic centre rather than a generic master’s label. In particular, Economics and empirical methods prepares the later master’s thesis, so the sequence cannot be reduced to a list of interchangeable electives.

The published groups include Economics and empirical methods, Data science methods, Specialisation and research, Master’s thesis. Their credit values show how the programme balances required study, choice and independent work. An elective heading does not guarantee that every named class runs in a chosen term.

Module availability, sequencing and recognition remain subject to the current examination rules and semester catalogue. This is the curriculum decision that deserves attention before enrolment. The current examination regulations and module catalogue govern the final study plan, credit recognition and thesis route.

Should an Indian student shortlist University of Oldenburg MSc Applied Economics and Data Science?

Shortlist MSc Applied Economics and Data Science when economics and empirical methods matches both your academic record and intended work. The recommendation is conditional because Oldenburg still checks subject content, language proof and documents. Resolve the module fit in writing before paying any application or relocation cost.

The strongest case connects prior preparation in economics and empirical methods with a credible plan for economic data analyst. That is more specific than applying because the award title sounds related to a previous degree. The official course description supplies the academic detail. The four-semester Master’s degree programme in Applied Economics and Data Science has a workload of 120 ECTS credits and is split into four subject areas. In the Economics component (36 ECTS credits), students learn about market mechanisms, international trade, financial markets, development economics, climate, energy and resource economics in the two compulsory modules Advanced Microeconomics and Industrial Organisation as well as in the three elective modules. In the Empirical Methods component (18 ECTS credits), students learn advanced methods in the fields of econometrics, statistics and simulation. These constitute the basis of all empirical research in economics and meet contemporary methodological requirements. In the Data Science modules (18 ECTS credits), students are taught current methods of data management, machine learning and deep learning, and they learn how to apply these techniques for conducting analyses in the field of economics. The Specialisation elective modules (18 ECTS credits) give students the opportunity to develop their own individual specialisation profile. They can choose courses from the Economics, Empirical Methods and Data Science components. Students can also take other modules in Business Administration, Law and Computer Science to create a specialisation profile that matches their own interests and career aspirations. The design and evaluation of government interventions in markets to ensure that they function properly or to achieve societal goals has always been a cornerstone of economics. A classic example, which is currently the subject of controversial public debate, is the use of market regulation to protect the environment, for example through the introduction of taxes or the expansion of certificate trading to reduce CO2 emissions. There are many more examples in areas such as development policy, foreign trade, the housing market and financial markets. In all of these fields, the evaluation of interventions requires huge amounts of data and a combination of modern empirical methods, such as econometric estimates, simulation techniques and Big Data processing and analysis methods. This degree programme, which is at the crossroads between economics and computer science, acknowledges the fact that empirical methods for analysing data in both disciplines are becoming increasingly similar. Due to the ever-growing data sets used to analyse economic issues, methods for analysing Big Data are increasingly finding their way into economics. The Master’s degree programme in Applied Economics and Data Science combines the fields of economics and computer science. In this degree programme, students acquire in-depth knowledge of theoretical concepts and empirical findings on government regulation and in-depth methodological knowledge of modern analytical procedures for empirical data. They learn how to prepare, analyse and interpret large data sets. The emphasis of this programme is on learning, applying and critically questioning methods and concepts used in current research to analyse and solve economic issues using empirical data. This Master’s degree programme in Applied Economics and Data Science is a research-oriented programme in which students are systematically introduced to the current state of research and in which they conduct a self-designed research project. After graduation, students are in a strong position to make their own contribution to research. The modules offered as part of the Master’s degree programme in Applied Economics and Data Science comprise a mix of lectures, seminars and practical exercises. Research-oriented learning modules are also offered. The current official module catalogue names wir821 International Trade, Production and Change; wir823 International Finance and Exchange Rate Economics; wir873 Applied Economics; wir874 Advanced Microeconomics; wir876 Topics in Economic Research; wir878 Public Economics and Market Design; wir901 Environmental Economics; wir889 Applied Environmental Economics; wir890 Climate Economics; wir893 Development Economics; wir895 Industrial Organization; wir922 Topics in Industrial Organization; wir751 Study Abroad I; wir752 Study Abroad II; wir753 Study Abroad III; wir760 Computable General Equlibrium Analysis; wir875 Prognoseverfahren; wir887 Advanced Econometrics; wir888 Applied Econometrics Using GIS Techniques; wir891 Complex Data Analysis; wir892 Computational Economics; wir894 Econometrics of Policy Evaluation; wir897 Spatial Econometrics; inf535 Computational Intelligence I; inf536 Computational Intelligence II; inf604 Business Intelligence I; inf607 Business Intelligence II; inf040 Introduction to Data Science; inf962 Fundamental Competencies in Computing Science III: Algorithms and Computational Problem Solving; inf510 Energieinformationssysteme; wir842 Banking; wir843 Financial Risk Management; wir886 Digital Transformation: Strategies and Sustainability; wir896 Operations Management; wir898 Strategic Sustainability Management; wir899 Supply Chain Management; wir921 Sustainable Supply Chain Management; wir806 Informationstechnologierecht; inf530 Künstliche Intelligenz; inf5114 Digitalised Energy System Requirements Engineering; wir923 Advanced Research Topics in Sustainable Supply Chain Management; wir847 Advanced Managerial Accounting; wir837 Advanced Corporate Finance; wir841 Advanced Financial Accounting; inf109 Datenbanken III; inf007 Datenbanken I.

The principal rejection risk is a transcript that cannot support the programme's named academic foundation. Cost, housing, visa and employment are separate decisions after academic fit has been established.

Decision checkscomplete cost · entry fit · application timing · outcome evidence

Sources

These sources support the programme, admission, cost and immigration information used on this page.

Sources checked on September 4, 2026. The next intake covered here is Winter 2027/28.