best universities for phd in data science in europe

Best Universities for Data Science in Europe

Updated: February 29, 2024

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Below is a list of best universities in Europe ranked based on their research performance in Data Science. A graph of 8.92M citations received by 333K academic papers made by 727 universities in Europe was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. University College London

For Data Science

2. University of Oxford

3. Imperial College London

4. University of Bristol

5. University of Manchester

6. University of Cambridge

7. University of Edinburgh

8. University of Southampton

9. University of Birmingham

10. King's College London

11. St George's, University of London

12. University of Sheffield

13. Catholic University of Leuven

14. University of York

15. University of Amsterdam

16. University of Glasgow

17. University of Liverpool

18. Swiss Federal Institute of Technology Zurich

19. University of London

20. Newcastle University

21. Leiden University

22. Delft University of Technology

23. University of Nottingham

24. University of Leeds

25. Federal Institute of Technology Lausanne

26. University of Zurich

27. Eindhoven University of Technology

28. University of Warwick

29. University of Leicester

30. Polytechnic University of Milan

31. Cardiff University

32. Technical University of Munich

33. University of Granada

34. Utrecht University

35. Uppsala University

36. Radboud University

37. Queen Mary University of London

38. University of Exeter

39. Technical University of Madrid

40. University of Bologna

41. Claude Bernard University Lyon 1

42. Vienna University of Technology

43. University of Copenhagen

44. Heidelberg University - Germany

45. Free University Amsterdam

46. Ghent University

47. University of Aberdeen

48. Technical University of Catalonia

49. University of Helsinki

50. University of Geneva

51. University of Pisa

52. RWTH Aachen University

53. University College Dublin

54. Sapienza University of Rome

55. Maastricht University

56. KTH Royal Institute of Technology

57. Lancaster University

58. Federico II University of Naples

59. Karlsruhe Institute of Technology

60. Polytechnic University of Valencia

61. University of Twente

62. Erasmus University Rotterdam

63. Norwegian University of Science and Technology

64. University of Bern

65. University of Stuttgart

66. London School of Economics and Political Science

67. University of Groningen

68. Polytechnic University of Bari

69. Aalto University

70. University of Porto

71. Technical University of Berlin

72. Ulster University

73. University of Wales

74. University of Patras

75. University of Oslo

76. Pierre and Marie Curie University

77. University of Dundee

78. Swansea University

79. Keele University

80. Aarhus University

81. National Technical University of Athens

82. Durham University

83. Lund University

84. University of Munich

85. City, University of London

86. Queen's University Belfast

87. Aalborg University

88. University of Surrey

89. University of Sussex

90. University of Vienna

91. University of Milan

92. University of Reading

93. Dresden University of Technology

94. Brunel University London

95. Wageningen University

96. University of East Anglia

97. Technical University of Denmark

98. University of Leipzig

99. Karolinska Institute

100. University of Padua

Computer Science subfields in Europe

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Applied Data Science

For students interested in research, the MSc degree provides the opportunity to start a PhD research project in any of the related topics at a university in the Netherlands or abroad. Such positions are regularly available within Utrecht University. There are ample contacts with other universities as well, partly through the nationwide Dutch research school SIKS (School for Knowledge and Information Systems). Some positions are sponsored by companies or the Dutch research council. Graduates may also find challenging positions in R&D departments of international companies, governments, and the banking and insurance sectors.

Doing a PhD

If you have completed your Master's programme, and you are enthusiastic about doing research in your field, then maybe doing a Doctorate (PhD) will interest you. A Doctor’s degree is the highest academic degree awarded by a Dutch university. You start as 'assistant in training' (aio) or 'researcher in training' (oio).

At Utrecht University

At Utrecht University you take part in education in one of the Graduate Schools and often also teach students. During the four-year PhD programme you work under the guidance of a professor on creating a research project that results in a dissertation or a series of articles in scientific journals. You can search for positions on research projects on offer or a position whereby you are free to submit your own research proposal. Read more on doing a  PhD  at Utrecht University. 

Other options

The best way to find a PhD position is through networking with the professor in the field you wish to specialize. Another option is to search via  www.academictransfer.nl . Here you can also find more information on doing PhD research in the Netherlands. 

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(in collaboration with scuola normale superiore, sant’anna school, university of pisa and national research council).

The Program

The PhD in Data Science is aimed at educating the new generation of researchers that combine their disciplinary competences with those of a “data scientist”, able to exploit data and models for advancing knowledge in their own disciplines, or across diverse disciplines. To this purpose, the PhD in Data Science develops a mix of knowledge and skills on the methods and technologies for the management of large, heterogeneous and complex data, for data sensing ( how to harvest data ), for data analysis and mining ( how to make sense of data ), for data visualization and storytelling ( how to narrate data ), for understanding the ethical issues and the social impact of Data Science. The PhD students will have the opportunity of developing data science projects in a variety of domains, including:

• Data science for society and policy
• Data science for economics and finance
• Data science for culture and the humanities
• Data science for industry and manufacturing
• Data science for biology and health
• Data science for the hard and environmental sciences
• Data science ethics and legal aspects
• Data science techniques and methods

The PhD leverages the critical mass of data science labs and researchers accumulated in Pisa since early 2000’s, across the University of Pisa, the ISTI and IIT institutes of the CNR (National Research Council), Scuola Normale Superiore, Sant’Anna School of Advanced Studies and the IMT School for Advanced Studies Lucca. These labs gave rise to pioneering European projects in big data analytics and data science, as well as to the earliest educational programs for data scientists at graduate and PhD level. In 2015, the European Commission has chosen this hub as the coordinator of the European Research Infrastructure for Big Data Analytics & Social Mining,  SoBigData     http://www.sobigdata.eu .  This initiative provides an ecosystem of data, analytics and competences to support inter-disciplinary open data science and data-driven innovation, within an ethical framework of transparency, privacy, and responsibility. SoBigData provides a unique platform for doctoral education in Data Science, recognized by the Ministry of Education, University and Research   [1] , where PhD students can carry out multi-disciplinary data-driven research.

The IMT School Representative for the Program is Prof. Rocco De Nicola .

   [1]  Rapporto MIUR BigData,    http://www.istruzione.it/allegati/2016/bigdata.pdf   pag. 33

For further information, please visit the   Program's website .

Teaching Activity

Teaching is articulated in two lines: alignment of data science skills, to create a common ground for students with diverse background, and applications of data science in disciplinary and multi-disciplinary contexts. For alignment, PhD students will have the opportunity to take selected courses offered by the post-graduate Master in “Big Data Analytics and Social Mining” (Master Big Data) of the University of Pisa, in collaboration with CNR, Scuola Normale Superiore, Sant’Anna School of Advanced Studies and SoBigData.eu. Available courses cover the basics of Data Science and Big Data Analytics:

• Big Data Sensing & Procurement (Analytical Web Crawling, Scraping, Web Search and Information Retrieval, Semantic Text Annotation, Big Data Sources, Crowdsensing)
• Big Data Mining (Data Mining, Machine Learning and Statistical Learning, Network Science and Social Network Analysis, Mobility Data Analysis, Web Mining, Nowcasting, Sentiment Analysis and Opinion Mining)
• Big Data Storytelling (Visualization, Visual analytics, Data Journalism)
• Big Data Ethics (Privacy-by-design, Data Protection Regulations, Responsible Data Science, Legal aspects of Data Science)
• Big Data Technologies (Data Management for Business Intelligence, High Performance & Scalable Analytics, NO-SQL Big Data Platforms).

A wide variety of PhD courses focusing on the multi-disciplinary applications of data science are offered by the participating institutions, also in synergy with existing disciplinary PhD programs. Students also have the opportunity to participate in summer schools organized in collaboration with international research institutions, and to the PhD+ program of the University of Pisa, for the development of entrepreneurial and innovation skills.

The PhD Board

Dino Pedreschi   (PhD Program Coordinator), University of Pisa Albert-Laszlo Barabasi , Northeastern University, Boston, USA Vincenzo Barone , Scuola Normale Superiore Roberta Bracciale , University of Pisa Chiara Cappelli , Scuola Normale Superiore Alessandro Cellerino , Scuola Normale Superiore Francesca Chiaromonte , Sant’Anna school of Advanced Studies Giulio Cimini , IMT School for Advanced Studies Lucca Marco Conti , National Research Council (CNR) Tommaso Cucinotta , Sant’Anna school of Advanced Studies Giuseppe De Pietro , National Research Council (CNR) Fabio Gadducci , University of Pisa Diego Garlaschelli , IMT School for Advanced Studies Fosca Giannotti , National Research Council (CNR) János Kertész , Central European University, Budapest Fabrizio Lillo , Università di Bologna Pietro Luigi Lopalco , University of Pisa Francesco Marcelloni , University of Pisa Stan Matwin , Dalhousie University, Halifax, CDN Anna Monreale , University of Pisa Elena Pavan , Scuola Normale Superiore Alex “Sandy” Pentland , MIT, USA Raffaele Perego , National Research Council (CNR) Andrea Piccaluga , Sant’Anna school of Advanced Studies Nadia Pisanti , University of Pisa Monica Pratesi , University of Pisa Chiara Maria Angela Roda , University of Pisa Salvatore Ruggieri , University of Pisa Tiziano Squartini , IMT School for Advanced Studies Lucca Franco Turini , University of Pisa

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Details on upcoming and past calls for applications are available on the Program's website .

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2716 Study programs

Study Data Science in Germany: 92 Universities with 132 English Degree Programs

All important info for international students in germany (2024/2025).

Data Science is an interdisciplinary field of science that enables scientifically sound methods, processes, algorithms, and systems for extracting knowledge, patterns, and inferences from both structured and unstructured data.

Data Science uses techniques and theories from mathematics, statistics, and information technology, including signal processing, uses probability models of machine learning, statistical learning, programming, data science, pattern recognition, prognostics, uncertainty modeling, and data warehousing.

Individuals working in the field of Data Science are referred to as Data Scientists, although more specific or specializations of other, higher-level job titles are usually common (e.g., statistician, computer scientist).

Study Programs in English

Universities

Universities in International Rankings

€ 0 (79 programs for EU citizens, 69 programs for Non-EU citizens)

€ 10,000 per semester (4 programs for EU citizens/Non-EU)

Winter Semester

between May 31 and May 15

Summer Semester

Top-ranked German Universities in Data Science

private (state-approved) University

No. of Students: approx. 1,000 students

Program Fees: € 8,500 - € 9,875 (per semester)

private (state-approved) University of Applied Sciences

No. of Students: approx. 100,000 students

Program Fees: € 2,394 - € 5,975 (per semester)

No. of Students: approx. 400 students

Program Fees: € 7,390 - € 7,890 (per semester)

public University

No. of Students: approx. 51,000 students

Program Fees: € 0 (per semester)

public Technical University

No. of Students: approx. 53,000 students

Program Fees: € 0 - € 6,000 (per semester)

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Webinar video, study computer & data science in germany (2021) | webinar with deggendorf institute of technology & tu braunschweig.

This video is a recording of the webinar "Study Computer & Data Science in Germany" from May 5, 2021 - with two special guests:

• Deggendorf Institute of Technology: B.Sc. Artificial Intelligence  presented by Prof. Dr. Patrick Glauner (Full Professor of Artificial Intelligence) ​
• Technische Universität Braunschweig: M.Sc. Data Science presented by Prof. Dr. Ina Schaefer (Professor for the Institute for Software Engineering and Automotive Informatics)

3 English Degree Programs for Data Science in Germany

Kühne Logistics University Hamburg

International management.

Hochschule der Bayerischen Wirtschaft (HDBW) Munich

Digital business modeling and entrepreneurship - part time.

TU Dortmund University Dortmund

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Berlin Professional School Hochschule für Wirtschaft und Recht Berlin · Berlin

International business management.

HECTOR School of Engineering and Management Karlsruhe Institute of Technology (KIT) · Karlsruhe

Mobility systems engineering & management.

Digital Business Modeling and Entrepreneurship - Full time

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4 (1 program )

61 (3 programs )

B1 Preliminary (PET) (2 programs )

7 (16 programs )

108 (1 program )

C2 Proficiency (CPE) (20 programs )

Friedrich Schiller University Jena Jena

Mathematics.

Technische Universität Braunschweig Braunschweig

Computational sciences in engineering.

ifs Internationale Filmschule Köln / TH Köln - Cologne University of Applied Sciences Cologne

Digital narratives.

2-20 semesters

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List of all German Universities offering English-taught Study Programs in Data Science

Ansbach University of Applied Sciences

Program Fees: € 0

M.Eng. (Master of Engineering)

Aschaffenburg University of Applied Sciences

B.Sc. (Bachelor of Science)

Bauhaus-Universität Weimar

M.Sc. (Master of Science)

Berlin International University of Applied Sciences

Program Fees: € 4,050 - € 4,190

B.A. (Bachelor of Arts)

Berliner Hochschule für Technik (BHT)

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5 PhD Degrees in Technology Studies Data Science in Europe for 2024

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PhD Degrees in Technology Studies Data Science

Data science is a field of work in which professionals seek to extract meaningful information from large amounts of complex data in the search for solutions to business challenges. Coursework may focus on mathematics, statistics, programming, and the development of analytic skills.

In all, there are over 4000 Higher Education Institutions in Europe offering a wide range of courses at Bachelor, Masters and Doctorate level. With more and more of these organizations offering English as the language of education for at least some of their degree programs, universities in Europe are now of higher quality than ever before. Universities in Europe offer a friendly welcome to foreign students and to give a course of knowledge that meets their profession needs in today’s global demand.

Requirements for the PhD program often involve the student having already obtained a Master’s degree. Additionally, a thesis or dissertation primarily consisting of original academic research must be submitted. In some countries, this work may even need to be defended in front of a panel.

DiscoverDataScience.org

PhD in Data Science – Your Guide to Choosing a Doctorate Degree Program

Created by aasif.faizal

Professional opportunities in data science are growing incredibly fast. That’s great news for students looking to pursue a career as a data scientist. But it also means that there are a lot more options out there to investigate and understand before developing the best educational path for you.

A PhD is the most advanced data science degree you can get, reflecting a depth of knowledge and technical expertise that will put you at the top of your field.

This means that PhD programs are the most time-intensive degree option out there, typically requiring that students complete dissertations involving rigorous research. This means that PhDs are not for everyone. Indeed, many who work in the world of big data hold master’s degrees rather than PhDs, which tend to involve the same coursework as PhD programs without a dissertation component. However, for the right candidate, a PhD program is the perfect choice to become a true expert on your area of focus.

If you’ve concluded that a data science PhD is the right path for you, this guide is intended to help you choose the best program to suit your needs. It will walk through some of the key considerations while picking graduate data science programs and some of the nuts and bolts (like course load and tuition costs) that are part of the data science PhD decision-making process.

Data Science PhD vs. Masters: Choosing the right option for you

If you’re considering pursuing a data science PhD, it’s worth knowing that such an advanced degree isn’t strictly necessary in order to get good work opportunities. Many who work in the field of big data only hold master’s degrees, which is the level of education expected to be a competitive candidate for data science positions.

So why pursue a data science PhD?

Simply put, a PhD in data science will leave you qualified to enter the big data industry at a high level from the outset.

You’ll be eligible for advanced positions within companies, holding greater responsibilities, keeping more direct communication with leadership, and having more influence on important data-driven decisions. You’re also likely to receive greater compensation to match your rank.

However, PhDs are not for everyone. Dissertations require a great deal of time and an interest in intensive research. If you are eager to jumpstart a career quickly, a master’s program will give you the preparation you need to hit the ground running. PhDs are appropriate for those who want to commit their time and effort to schooling as a long-term investment in their professional trajectory.

For more information on the difference between data science PhD’s and master’s programs, take a look at our guide here.

Topics include:

• Can I get an Online Ph.D in Data Science?
• Overview of Ph.d Coursework

Preparing for a Doctorate Program

Building a solid track record of professional experience, things to consider when choosing a school.

• What Does it Cost to Get a Ph.D in Data Science?
• School Listings

Data Science PhD Programs, Historically

Historically, data science PhD programs were one of the main avenues to get a good data-related position in academia or industry. But, PhD programs are heavily research oriented and require a somewhat long term investment of time, money, and energy to obtain. The issue that some data science PhD holders are reporting, especially in industry settings, is that that the state of the art is moving so quickly, and that the data science industry is evolving so rapidly, that an abundance of research oriented expertise is not always what’s heavily sought after.

Instead, many companies are looking for candidates who are up to date with the latest data science techniques and technologies, and are willing to pivot to match emerging trends and practices.

One recent development that is making the data science graduate school decisions more complex is the introduction of specialty master’s degrees, that focus on rigorous but compact, professional training. Both students and companies are realizing the value of an intensive, more industry-focused degree that can provide sufficient enough training to manage complex projects and that are more client oriented, opposed to research oriented.

However, not all prospective data science PhD students are looking for jobs in industry. There are some pretty amazing research opportunities opening up across a variety of academic fields that are making use of new data collection and analysis tools. Experts that understand how to leverage data systems including statistics and computer science to analyze trends and build models will be in high demand.

Can You Get a PhD in Data Science Online?

While it is not common to get a data science Ph.D. online, there are currently two options for those looking to take advantage of the flexibility of an online program.

Indiana University Bloomington and Northcentral University both offer online Ph.D. programs with either a minor or specialization in data science.

Given the trend for schools to continue increasing online offerings, expect to see additional schools adding this option in the near future.

Overview of PhD Coursework

A PhD requires a lot of academic work, which generally requires between four and five years (sometimes longer) to complete.

Here are some of the high level factors to consider and evaluate when comparing data science graduate programs.

How many credits are required for a PhD in data science?

On average, it takes 71 credits to graduate with a PhD in data science — far longer (almost double) than traditional master’s degree programs. In addition to coursework, most PhD students also have research and teaching responsibilities that can be simultaneously demanding and really great career preparation.

What’s the core curriculum like?

In a data science doctoral program, you’ll be expected to learn many skills and also how to apply them across domains and disciplines. Core curriculums will vary from program to program, but almost all will have a core foundation of statistics.

All PhD candidates will have to take a qualifying exam. This can vary from university to university, but to give you some insight, it is broken up into three phases at Yale. They have a practical exam, a theory exam and an oral exam. The goal is to make sure doctoral students are developing the appropriate level of expertise.

Dissertation

One of the final steps of a PhD program involves presenting original research findings in a formal document called a dissertation. These will provide background and context, as well as findings and analysis, and can contribute to the understanding and evolution of data science. A dissertation idea most often provides the framework for how a PhD candidate’s graduate school experience will unfold, so it’s important to be thoughtful and deliberate while considering research opportunities.

Since data science is such a rapidly evolving field and because choosing the right PhD program is such an important factor in developing a successful career path, there are some steps that prospective doctoral students can take in advance to find the best-fitting opportunity.

Join professional associations

Even before being fully credentials, joining professional associations and organizations such as the Data Science Association and the American Association of Big Data Professionals is a good way to get exposure to the field. Many professional societies are welcoming to new members and even encourage student participation with things like discounted membership fees and awards and contest categories for student researchers. One of the biggest advantages to joining is that these professional associations bring together other data scientists for conference events, research-sharing opportunities, networking and continuing education opportunities.

Leverage your social network

Be on the lookout to make professional connections with professors, peers, and members of industry. There are a number of LinkedIn groups dedicated to data science. A well-maintained professional network is always useful to have when looking for advice or letters of recommendation while applying to graduate school and then later while applying for jobs and other career-related opportunities.

Kaggle competitions

Kaggle competitions provide the opportunity to solve real-world data science problems and win prizes. A list of data science problems can be found at Kaggle.com . Winning one of these competitions is a good way to demonstrate professional interest and experience.

Internships

Internships are a great way to get real-world experience in data science while also getting to work for top names in the world of business. For example, IBM offers a data science internship which would also help to stand out when applying for PhD programs, as well as in seeking employment in the future.

Demonstrating professional experience is not only important when looking for jobs, but it can also help while applying for graduate school. There are a number of ways for prospective students to gain exposure to the field and explore different facets of data science careers.

Get certified

There are a number of data-related certificate programs that are open to people with a variety of academic and professional experience. DeZyre has an excellent guide to different certifications, some of which might help provide good background for graduate school applications.

Conferences

Conferences are a great place to meet people presenting new and exciting research in the data science field and bounce ideas off of newfound connections. Like professional societies and organizations, discounted student rates are available to encourage student participation. In addition, some conferences will waive fees if you are presenting a poster or research at the conference, which is an extra incentive to present.

It can be hard to quantify what makes a good-fit when it comes to data science graduate school programs. There are easy to evaluate factors, such as cost and location, and then there are harder to evaluate criteria such as networking opportunities, accessibility to professors, and the up-to-dateness of the program’s curriculum.

Nevertheless, there are some key relevant considerations when applying to almost any data science graduate program.

What most schools will require when applying:

• All undergraduate and graduate transcripts
• A statement of intent for the program (reason for applying and future plans)
• Letters of reference
• Application fee
• Online application
• A curriculum vitae (outlining all of your academic and professional accomplishments)

What Does it Cost to Get a PhD in Data Science?

The great news is that many PhD data science programs are supported by fellowships and stipends. Some are completely funded, meaning the school will pay tuition and basic living expenses. Here are several examples of fully funded programs:

• University of Southern California
• University of Nevada, Reno
• Kennesaw State University
• Worcester Polytechnic Institute
• University of Maryland

For all other programs, the average range of tuition, depending on the school can range anywhere from $1,300 per credit hour to $2,000 amount per credit hour. Remember, typical PhD programs in data science are between 60 and 75 credit hours, meaning you could spend up to $150,000 over several years.

That’s why the financial aspects are so important to evaluate when assessing PhD programs, because some schools offer full stipends so that you are able to attend without having to find supplemental scholarships or tuition assistance.

Can I become a professor of data science with a PhD.? Yes! If you are interested in teaching at the college or graduate level, a PhD is the degree needed to establish the full expertise expected to be a professor. Some data scientists who hold PhDs start by entering the field of big data and pivot over to teaching after gaining a significant amount of work experience. If you’re driven to teach others or to pursue advanced research in data science, a PhD is the right degree for you.

Do I need a master’s in order to pursue a PhD.? No. Many who pursue PhDs in Data Science do not already hold advanced degrees, and many PhD programs include all the coursework of a master’s program in the first two years of school. For many students, this is the most time-effective option, allowing you to complete your education in a single pass rather than interrupting your studies after your master’s program.

Can I choose to pursue a PhD after already receiving my master’s? Yes. A master’s program can be an opportunity to get the lay of the land and determine the specific career path you’d like to forge in the world of big data. Some schools may allow you to simply extend your academic timeline after receiving your master’s degree, and it is also possible to return to school to receive a PhD if you have been working in the field for some time.

If a PhD. isn’t necessary, is it a waste of time? While not all students are candidates for PhDs, for the right students – who are keen on doing in-depth research, have the time to devote to many years of school, and potentially have an interest in continuing to work in academia – a PhD is a great choice. For more information on this question, take a look at our article Is a Data Science PhD. Worth It?

Complete List of Data Science PhD Programs

Below you will find the most comprehensive list of schools offering a doctorate in data science. Each school listing contains a link to the program specific page, GRE or a master’s degree requirements, and a link to a page with detailed course information.

Note that the listing only contains true data science programs. Other similar programs are often lumped together on other sites, but we have chosen to list programs such as data analytics and business intelligence on a separate section of the website.

Boise State University  – Boise, Idaho PhD in Computing – Data Science Concentration

The Data Science emphasis focuses on the development of mathematical and statistical algorithms, software, and computing systems to extract knowledge or insights from data.  

In 60 credits, students complete an Introduction to Graduate Studies, 12 credits of core courses, 6 credits of data science elective courses, 10 credits of other elective courses, a Doctoral Comprehensive Examination worth 1 credit, and a 30-credit dissertation.

Electives can be taken in focus areas such as Anthropology, Biometry, Ecology/Evolution and Behavior, Econometrics, Electrical Engineering, Earth Dynamics and Informatics, Geoscience, Geostatistics, Hydrology and Hydrogeology, Materials Science, and Transportation Science.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $7,236 total (Resident), $24,573 total (Non-resident)

View Course Offerings

Bowling Green State University  – Bowling Green, Ohio Ph.D. in Data Science

Data Science students at Bowling Green intertwine knowledge of computer science with statistics.

Students learn techniques in analyzing structured, unstructured, and dynamic datasets.

Courses train students to understand the principles of analytic methods and articulating the strengths and limitations of analytical methods.

The program requires 60 credit hours in the studies of Computer Science (6 credit hours), Statistics (6 credit hours), Data Science Exploration and Communication, Ethical Issues, Advanced Data Mining, and Applied Data Science Experience.

Students must also complete 21 credit hours of elective courses, a qualifying exam, a preliminary exam, and a dissertation.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $8,418 (Resident), $14,410 (Non-resident)

Brown University  – Providence, Rhode Island PhD in Computer Science – Concentration in Data Science

Brown University’s database group is a world leader in systems-oriented database research; they seek PhD candidates with strong system-building skills who are interested in researching TupleWare, MLbase, MDCC, Crowd DB, or PIQL.

In order to gain entrance, applicants should consider first doing a research internship at Brown with this group. Other ways to boost an application are to take and do well at massive open online courses, do an internship at a large company, and get involved in a large open-source software project.

Coding well in C++ is preferred.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $62,680 total

Chapman University  – Irvine, California Doctorate in Computational and Data Sciences

Candidates for the doctorate in computational and data science at Chapman University begin by completing 13 core credits in basic methodologies and techniques of computational science.

Students complete 45 credits of electives, which are personalized to match the specific interests and research topics of the student.

Finally, students complete up to 12 credits in dissertation research.

Applicants must have completed courses in differential equations, data structures, and probability and statistics, or take specific foundation courses, before beginning coursework toward the PhD.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $37,538 per year

Clemson University / Medical University of South Carolina (MUSC) – Joint Program – Clemson, South Carolina & Charleston, South Carolina Doctor of Philosophy in Biomedical Data Science and Informatics – Clemson

The PhD in biomedical data science and informatics is a joint program co-authored by Clemson University and the Medical University of South Carolina (MUSC).

Students choose one of three tracks to pursue: precision medicine, population health, and clinical and translational informatics. Students complete 65-68 credit hours, and take courses in each of 5 areas: biomedical informatics foundations and applications; computing/math/statistics/engineering; population health, health systems, and policy; biomedical/medical domain; and lab rotations, seminars, and doctoral research.

Applicants must have a bachelor’s in health science, computing, mathematics, statistics, engineering, or a related field, and it is recommended to also have competency in a second of these areas.

Program requirements include a year of calculus and college biology, as well as experience in computer programming.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $10,858 total (South Carolina Resident), $22,566 total (Non-resident)

View Course Offerings – Clemson

George Mason University  – Fairfax, Virginia Doctor of Philosophy in Computational Sciences and Informatics – Emphasis in Data Science

George Mason’s PhD in computational sciences and informatics requires a minimum of 72 credit hours, though this can be reduced if a student has already completed a master’s. 48 credits are toward graduate coursework, and an additional 24 are for dissertation research.

Students choose an area of emphasis—either computer modeling and simulation or data science—and completed 18 credits of the coursework in this area. Students are expected to completed the coursework in 4-5 years.

Applicants to this program must have a bachelor’s degree in a natural science, mathematics, engineering, or computer science, and must have knowledge and experience with differential equations and computer programming.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $13,426 total (Virginia Resident), $35,377 total (Non-resident)

Harrisburg University of Science and Technology  – Harrisburg, Pennsylvania Doctor of Philosophy in Data Sciences

Harrisburg University’s PhD in data science is a 4-5 year program, the first 2 of which make up the Harrisburg master’s in analytics.

Beyond this, PhD candidates complete six milestones to obtain the degree, including 18 semester hours in doctoral-level courses, such as multivariate data analysis, graph theory, machine learning.

Following the completion of ANLY 760 Doctoral Research Seminar, students in the program complete their 12 hours of dissertation research bringing the total program hours to 36.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $14,940 total

Icahn School of Medicine at Mount Sinai  – New York, New York Genetics and Data Science, PhD

As part of the Biomedical Science PhD program, the Genetics and Data Science multidisciplinary training offers research opportunities that expand on genetic research and modern genomics. The training also integrates several disciplines of biomedical sciences with machine learning, network modeling, and big data analysis.

Students in the Genetics and Data Science program complete a predetermined course schedule with a total of 64 credits and 3 years of study.

Additional course requirements and electives include laboratory rotations, a thesis proposal exam and thesis defense, Computer Systems, Intro to Algorithms, Machine Learning for Biomedical Data Science, Translational Genomics, and Practical Analysis of a Personal Genome.

Delivery Method: Campus GRE: Not Required 2022-2023 Tuition: $31,303 total

Indiana University-Purdue University Indianapolis  – Indianapolis, Indiana PhD in Data Science PhD Minor in Applied Data Science

Doctoral candidates pursuing the PhD in data science at Indiana University-Purdue must display competency in research, data analytics, and at management and infrastructure to earn the degree.

The PhD is comprised of 24 credits of a data science core, 18 credits of methods courses, 18 credits of a specialization, written and oral qualifying exams, and 30 credits of dissertation research. All requirements must be completed within 7 years.

Applicants are generally expected to have a master’s in social science, health, data science, or computer science. 

Currently a majority of the PhD students at IUPUI are funded by faculty grants and two are funded by the federal government. None of the students are self funded.

IUPUI also offers a PhD Minor in Applied Data Science that is 12-18 credits. The minor is open to students enrolled at IUPUI or IU Bloomington in a doctoral program other than Data Science.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $9,228 per year (Indiana Resident), $25,368 per year (Non-resident)

Jackson State University – Jackson, Mississippi PhD Computational and Data-Enabled Science and Engineering

Jackson State University offers a PhD in computational and data-enabled science and engineering with 5 concentration areas: computational biology and bioinformatics, computational science and engineering, computational physical science, computation public health, and computational mathematics and social science.

Students complete 12 credits of common core courses, 12 credits in the specialization, 24 credits of electives, and 24 credits in dissertation research.

Students may complete the doctoral program in as little as 5 years and no more than 8 years.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $8,270 total

Kennesaw State University  – Kennesaw, Georgia PhD in Analytics and Data Science

Students pursuing a PhD in analytics and data science at Kennesaw State University must complete 78 credit hours: 48 course hours and 6 electives (spread over 4 years of study), a minimum 12 credit hours for dissertation research, and a minimum 12 credit-hour internship.

Prior to dissertation research, the comprehensive examination will cover material from the three areas of study: computer science, mathematics, and statistics.

Successful applicants will have a master’s degree in a computational field, calculus I and II, programming experience, modeling experience, and are encouraged to have a base SAS certification.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $5,328 total (Georgia Resident), $19,188 total (Non-resident)

New Jersey Institute of Technology  – Newark, New Jersey PhD in Business Data Science

Students may enter the PhD program in business data science at the New Jersey Institute of Technology with either a relevant bachelor’s or master’s degree. Students with bachelor’s degrees begin with 36 credits of advanced courses, and those with master’s take 18 credits before moving on to credits in dissertation research.

Core courses include business research methods, data mining and analysis, data management system design, statistical computing with SAS and R, and regression analysis.

Students take qualifying examinations at the end of years 1 and 2, and must defend their dissertations successfully by the end of year 6.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $21,932 total (New Jersey Resident), $32,426 total (Non-resident)

New York University  – New York, New York PhD in Data Science

Doctoral candidates in data science at New York University must complete 72 credit hours, pass a comprehensive and qualifying exam, and defend a dissertation with 10 years of entering the program.

Required courses include an introduction to data science, probability and statistics for data science, machine learning and computational statistics, big data, and inference and representation.

Applicants must have an undergraduate or master’s degree in fields such as mathematics, statistics, computer science, engineering, or other scientific disciplines. Experience with calculus, probability, statistics, and computer programming is also required.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $37,332 per year

View Course Offering

Northcentral University  – San Diego, California PhD in Data Science-TIM

Northcentral University offers a PhD in technology and innovation management with a specialization in data science.

The program requires 60 credit hours, including 6-7 core courses, 3 in research, a PhD portfolio, and 4 dissertation courses.

The data science specialization requires 6 courses: data mining, knowledge management, quantitative methods for data analytics and business intelligence, data visualization, predicting the future, and big data integration.

Applicants must have a master’s already.

Delivery Method: Online GRE: Required 2022-2023 Tuition: $16,794 total

Stevens Institute of Technology – Hoboken, New Jersey Ph.D. in Data Science

Stevens Institute of Technology has developed a data science Ph.D. program geared to help graduates become innovators in the space.

The rigorous curriculum emphasizes mathematical and statistical modeling, machine learning, computational systems and data management.

The program is directed by Dr. Ted Stohr, a recognized thought leader in the information systems, operations and business process management arenas.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $39,408 per year

University at Buffalo – Buffalo, New York PhD Computational and Data-Enabled Science and Engineering

The curriculum for the University of Buffalo’s PhD in computational and data-enabled science and engineering centers around three areas: data science, applied mathematics and numerical methods, and high performance and data intensive computing. 9 credit course of courses must be completed in each of these three areas. Altogether, the program consists of 72 credit hours, and should be completed in 4-5 years. A master’s degree is required for admission; courses taken during the master’s may be able to count toward some of the core coursework requirements.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $11,310 per year (New York Resident), $23,100 per year (Non-resident)

University of Colorado Denver – Denver, Colorado PhD in Big Data Science and Engineering

The University of Colorado – Denver offers a unique program for those students who have already received admission to the computer science and information systems PhD program.

The Big Data Science and Engineering (BDSE) program is a PhD fellowship program that allows selected students to pursue research in the area of big data science and engineering. This new fellowship program was created to train more computer scientists in data science application fields such as health informatics, geosciences, precision and personalized medicine, business analytics, and smart cities and cybersecurity.

Students in the doctoral program must complete 30 credit hours of computer science classes beyond a master’s level, and 30 credit hours of dissertation research.

The BDSE fellowship requires students to have an advisor both in the core disciplines (either computer science or mathematics and statistics) as well as an advisor in the application discipline (medicine and public health, business, or geosciences).

In addition, the fellowship covers full stipend, tuition, and fees up to ~50k for BDSE fellows annually. Important eligibility requirements can be found here.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $55,260 total

University of Marylan d  – College Park, Maryland PhD in Information Studies

Data science is a potential research area for doctoral candidates in information studies at the University of Maryland – College Park. This includes big data, data analytics, and data mining.

Applicants for the PhD must have taken the following courses in undergraduate studies: programming languages, data structures, design and analysis of computer algorithms, calculus I and II, and linear algebra.

Students must complete 6 qualifying courses, 2 elective graduate courses, and at least 12 credit hours of dissertation research.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $16,238 total (Maryland Resident), $35,388 total (Non-resident)

University of Massachusetts Boston  – Boston, Massachusetts PhD in Business Administration – Information Systems for Data Science Track

The University of Massachusetts – Boston offers a PhD in information systems for data science. As this is a business degree, students must complete coursework in their first two years with a focus on data for business; for example, taking courses such as business in context: markets, technologies, and societies.

Students must take and pass qualifying exams at the end of year 1, comprehensive exams at the end of year 2, and defend their theses at the end of year 4.

Those with a degree in statistics, economics, math, computer science, management sciences, information systems, and other related fields are especially encouraged, though a quantitative degree is not necessary.

Students accepted by the program are ordinarily offered full tuition credits and a stipend ($25,000 per year) to cover educational expenses and help defray living costs for up to three years of study.

During the first two years of coursework, they are assigned to a faculty member as a research assistant; for the third year students will be engaged in instructional activities. Funding for the fourth year is merit-based from a limited pool of program funds

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $18,894 total (in-state), $36,879 (out-of-state)

University of Nevada Reno – Reno, Nevada PhD in Statistics and Data Science

The University of Nevada – Reno’s doctoral program in statistics and data science is comprised of 72 credit hours to be completed over the course of 4-5 years. Coursework is all within the scope of statistics, with titles such as statistical theory, probability theory, linear models, multivariate analysis, statistical learning, statistical computing, time series analysis.

The completion of a Master’s degree in mathematics or statistics prior to enrollment in the doctoral program is strongly recommended, but not required.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $5,814 total (in-state), $22,356 (out-of-state)

University of Southern California – Los Angles, California PhD in Data Sciences & Operations

USC Marshall School of Business offers a PhD in data sciences and operations to be completed in 5 years.

Students can choose either a track in operations management or in statistics. Both tracks require 4 courses in fall and spring of the first 2 years, as well as a research paper and courses during the summers. Year 3 is devoted to dissertation preparation and year 4 and/or 5 to dissertation defense.

A bachelor’s degree is necessary for application, but no field or further experience is required.

Students should complete 60 units of coursework. If the students are admitted with Advanced Standing (e.g., Master’s Degree in appropriate field), this requirement may be reduced to 40 credits.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $63,468 total

University of Tennessee-Knoxville  – Knoxville, Tennessee The Data Science and Engineering PhD

The data science and engineering PhD at the University of Tennessee – Knoxville requires 36 hours of coursework and 36 hours of dissertation research. For those entering with an MS degree, only 24 hours of course work is required.

The core curriculum includes work in statistics, machine learning, and scripting languages and is enhanced by 6 hours in courses that focus either on policy issues related to data, or technology entrepreneurship.

Students must also choose a knowledge specialization in one of these fields: health and biological sciences, advanced manufacturing, materials science, environmental and climate science, transportation science, national security, urban systems science, and advanced data science.

Applicants must have a bachelor’s or master’s degree in engineering or a scientific field. 

All students that are admitted will be supported by a research fellowship and tuition will be included.

Many students will perform research with scientists from Oak Ridge national lab, which is located about 30 minutes drive from campus.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $11,468 total (Tennessee Resident), $29,656 total (Non-resident)

University of Vermont – Burlington, Vermont Complex Systems and Data Science (CSDS), PhD

Through the College of Engineering and Mathematical Sciences, the Complex Systems and Data Science (CSDS) PhD program is pan-disciplinary and provides computational and theoretical training. Students may customize the program depending on their chosen area of focus.

Students in this program work in research groups across campus.

Core courses include Data Science, Principles of Complex Systems and Modeling Complex Systems. Elective courses include Machine Learning, Complex Networks, Evolutionary Computation, Human/Computer Interaction, and Data Mining.

The program requires at least 75 credits to graduate with approval by the student graduate studies committee.

Delivery Method: Campus GRE: Not Required 2022-2023 Tuition: $12,204 total (Vermont Resident), $30,960 total (Non-resident)

University of Washington Seattle Campus – Seattle, Washington PhD in Big Data and Data Science

The University of Washington’s PhD program in data science has 2 key goals: training of new data scientists and cyberinfrastructure development, i.e., development of open-source tools and services that scientists around the world can use for big data analysis.

Students must take core courses in data management, machine learning, data visualization, and statistics.

Students are also required to complete at least one internship that covers practical work in big data.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $17,004 per year (Washington resident), $30,477 (non-resident)

University of Wisconsin-Madison – Madison, Wisconsin PhD in Biomedical Data Science

The PhD program in Biomedical Data Science offered by the Department of Biostatistics and Medical Informatics at UW-Madison is unique, in blending the best of statistics and computer science, biostatistics and biomedical informatics. 

Students complete three year-long course sequences in biostatistics theory and methods, computer science/informatics, and a specialized sequence to fit their interests.

Students also complete three research rotations within their first two years in the program, to both expand their breadth of knowledge and assist in identifying a research advisor.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $10,728 total (in-state), $24,054 total (out-of-state)

Vanderbilt University – Nashville, Tennessee Data Science Track of the BMI PhD Program

The PhD in biomedical informatics at Vanderbilt has the option of a data science track.

Students complete courses in the areas of biomedical informatics (3 courses), computer science (4 courses), statistical methods (4 courses), and biomedical science (2 courses). Students are expected to complete core courses and defend their dissertations within 5 years of beginning the program.

Applicants must have a bachelor’s degree in computer science, engineering, biology, biochemistry, nursing, mathematics, statistics, physics, information management, or some other health-related field.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $53,160 per year

Washington University in St. Louis – St. Louis, Missouri Doctorate in Computational & Data Sciences

Washington University now offers an interdisciplinary Ph.D. in Computational & Data Sciences where students can choose from one of four tracks (Computational Methodologies, Political Science, Psychological & Brain Sciences, or Social Work & Public Health).

Students are fully funded and will receive a stipend for at least five years contingent on making sufficient progress in the program.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $59,420 total

Worcester Polytechnic Institute – Worcester, Massachusetts PhD in Data Science

The PhD in data science at Worcester Polytechnic Institute focuses on 5 areas: integrative data science, business intelligence and case studies, data access and management, data analytics and mining, and mathematical analysis.

Students first complete a master’s in data science, and then complete 60 credit hours beyond the master’s, including 30 credit hours of research.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $28,980 per year

Yale University – New Haven, Connecticut PhD Program – Department of Stats and Data Science

The PhD in statistics and data science at Yale University offers broad training in the areas of statistical theory, probability theory, stochastic processes, asymptotics, information theory, machine learning, data analysis, statistical computing, and graphical methods. Students complete 12 courses in the first year in these topics.

Students are required to teach one course each semester of their third and fourth years.

Most students complete and defend their dissertations in their fifth year.

Applicants should have an educational background in statistics, with an undergraduate major in statistics, mathematics, computer science, or similar field.

Delivery Method: Campus GRE: Required 2022-2023 Tuition: $46,900 total

• Related Programs

Best universities in Europe 2024

Times higher education world university rankings 2024 data reveal the top colleges in europe.

• Rankings for Students
• Study abroad

Top 10 universities in Europe 2024

Scroll down for the full list of best universities in Europe

European universities take just over 40 per cent of the places in the list of the best universities in the world.

Develop the skills top employers want while you study and get a digital certificate to boost your CV!

The  Times Higher Education  World University Rankings 2024  ranks 1,904 universities worldwide. More than 600 of them are in Europe.

A UK institution – the University of Oxford – takes the top spot in our Europe table (and in the overall rankings), while 102 other UK universities appear in the league table. Spain and Italy are also well represented, with 56 institutions each.

Of the universities in mainland Europe, a Swiss institution –  ETH Zurich  – achieves the highest rank, putting it in the top five in Europe and 11th in the THE World University Rankings 2024.

The top 10 European universities include UK, Swiss and German institutions, but UK universities take most of the top spots.

Best universities in the UK Best universities in France Best universities in Germany Best universities in the Netherlands Best universities in Italy Best universities in Spain Best universities in Ireland

Institutions were assessed on their teaching environment, research environment, citations (research influence), industry income and international outlook. The full methodology can be viewed here .

While Italy has 56 universities in the ranking, its top-ranked institution – the  University of Bologna  in joint 155th place – doesn’t make it into the top 50 in Europe.

Nordic countries also perform well, with Sweden and Finland punching above their weight relative to their population size, with 14 and 10 institutions respectively in the ranking. Sweden’s top university – Karolinska Institute  – makes the top 50 of the World University Rankings. The Netherlands also performs very strongly.

In the Europe table, other strong performers relative to their population size include Denmark (seven universities – led by the University of Copenhagen ) and the Republic of Ireland (nine universities in total).

Overall, more than 30 European countries are represented in the Europe 2024 ranking, including France, Greece, Poland and Portugal. 

Top 5 universities in Europe

UCL has its main campus in central London and has just opened a second campus at the Olympic Park in east London.

As well as being the first university to be established in London, UCL was the first in the UK to be entirely secular and admit students regardless of their religious beliefs. 

It has been a member of the League of European Research Universities since 2006 and is one of five British members (the others are the universities of Cambridge, Edinburgh, Oxford and Imperial College London ).

4. ETH Zurich

ETH Zurich is a science, technology, engineering and mathematics university.

The institute has produced more than 20 Nobel prizewinners, including Albert Einstein. 

About 35 per cent of the institution’s students are from abroad and the university has established an International Knowledge Base to forge research and teaching relationships across the world.

3. Imperial College London

Imperial College London is the only university in the UK to focus entirely on science, engineering, medicine and business. 

It attracts students from more than 125 countries and is considered one of the world’s most international universities .

In addition to top scientists, Fields medallists and Nobelists, Imperial also produces influential government advisers and policymakers. The author H. G. Wells and journalist and politician Sir Trevor Phillips are among Imperial’s famous alumni.

2. University of Cambridge

The University of Cambridge is a public research university in the UK, established in the 13th century. 

Like other ancient institutions, Cambridge has many traditions. Until 1909, a metre-long wooden spoon was presented to the student with the lowest passing honours grade in the final examinations of the mathematical tripos (one of the courses available at the university). The spoon is now on display in St John’s College.

1. University of Oxford

There is no specific date to mark the founding of the University of Oxford , but it is thought that it was established some time in the 13th century.

The university has the largest library system in the UK, with more than 11 million volumes.

It is one of the most  prestigious universities globally . However, women were not admitted until 1878, and it wasn’t until 1920 that women were awarded degrees. The last of the all-male colleges began accepting women in 1974.

It is home to a number of museums and galleries including the Ashmolean, the UK’s oldest museum and the world’s oldest university museum. It holds significant collections and works by artists such as Michelangelo, Turner and Picasso.

International perspective: a PhD student in Switzerland International perspective: an American student in Spain Studying in the Netherlands as an international student International perspective: from Hong Kong to Ireland Choosing a postgraduate degree in Paris International perspective: a Malaysian student in the UK

Best universities in Europe 2024: the results in full 

Click on each institution to view its  World University Rankings 2024  result

You can  search by country here  to make sure you find the right university for you

Editors note:  As part of our  THE statement on Ukraine  published on 2 March 2022, Russian universities have been given less prominence in our rankings. Russian and Belarusian universities that met the criteria for this ranking are not displayed in the table above.

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• Universities & Business Schools

The 9 Best Masters in Data Science in Europe

Data Science is a subject that is growing in popularity . Companies create a huge amount of data every day and will continue to do so in the future. As a consequence, there are plenty of opportunities for grads who know how to analyse data. But which are the best Masters in Data Science in Europe? We’ve decided to find out.

The year-on-year growth in data science job listings since 2019 is 37% . But the global tech talent shortage will grow to 85 million by 2030. This means that in the future there will be more opportunities in this sector.

If you’re planning on pursuing a career in data science, you’ll want to follow the best programme. Luckily, we’ve tracked down the 9 best Masters in Data Science in Europe. From Germany to the UK, these are the programmes that will give you a headstart in your data science career.

Best Masters in Data Science in Europe: What are they?

9. master in data science and advanced analytics, with a data science major at nova information management school (portugal).

The Master’s programme at Nova IMS in Lisbon focuses on big data and computational science. First-year courses include Machine Learning, Data Mining, and Big Data Analytics. There are also elective data science modules if you want to go deeper into niche subjects. The programme’s biggest attraction though is the work experience opportunities that are available. The best first-year students have the chance to complete a 6-month paid internship at a partner institution where they’ll get real-life work experience in data science.

8. Master in Computing Science: Data Science at Radboud University (Netherlands)

Radboud University’s Data Science programme is a specialisation on their Computing Science degree. Taught by the Institute for Computing and Informational Sciences, the two-year programme covers all aspects of data science. This includes machine learning and Bayesian networks to philosophy and ethics for computing science. You’ll also have the option to take electives in related areas like chemistry, biophysics, and language studies to complement your degree. Students who excel in the programme can also complete a dual degree in Data Science and Artificial Intelligence over three years. With this, you’ll gain skills that may be crucial in the future.

7. Master in Data Science at Rome Business School (Italy)

The Data Science Masters at Rome Business School has a broad curriculum – students study scientific processes in data science as well as managerial skills. Consequently, students get a well-rounded look at the business aspects of data science. After graduating, you should be ready to take on senior positions in organisations as well as technical roles in data science. One of the standout parts of the programme is the international boot camps in Rome and Barcelona, giving you the chance to work with many other students from Europe.

6. MSc Data Science at IU International University of Applied Science (Germany)

The Masters in Data Science at IU International University is one of the most affordable around €183 per month for the full-time, 12-month programme. Students can also complete a dual degree with London South Bank University, graduating with both a German and British degree. With 35,000 students from 110 nations studying at the university, you’ll get an international experience while studying the technical aspects of data science. Compulsory modules include Python programming, machine learning, big data, and cyber security – so you’ll get a broad overview of everything data science can do.

5. MSc Business Intelligence & Data Science at International School of Management (ISM) (Germany)

Students at ISM offers flexibility lacking from other Master’s programmes. Students can study in the city of their choice: Dortmund, Munich, Hamburg, or Stuttgart. The ISM curriculum focuses on a blend of technical skills and creativity; students will also follow modules on consulting and business analysis alongside software engineering and database systems courses. ISM is one of the best private universities in Germany and attracts students from as many as 75 different nationalities.

4. Master in Data Science at ETH ZÜrich (Switzerland)

The Master in Data Science at ETH Zürich is taught in collaboration with the Mathematics and Electrical Engineering departments, so it definitely embraces the technical side of this niche subject. The two-year programme centres around advanced subjects like neural network theory, advanced machine learning and algorithms. Students also spend time in the Data Science Lab, where they will gain hands-on experience with real-life data.

3. Master in Data Science and Management at LUISS University (Italy)

LUISS’ programme features a blend of technical data skills and economics. Students will follow courses on the digital economy and data protection law, as well as statistics and data visualisation. This unique pairing creates students skilled in both data science and business – a useful pairing for future jobs. With under 10,000 students, LUISS has a strong community with a big international population. So, it’s a great place to network and look for future opportunities in both Rome and the rest of Europe.

2. MSc Data Science at the University of Edinburgh (UK)

If you’re looking for a Masters in Data Science in the UK , then the University of Edinburgh is the place to go. The one-year programme covers all aspects of data science including extreme computing and accelerated neural language processing. As well as the subject matter, you’ll be joining a prestigious university. The University of Edinburgh  ranks as one of the best universities in the UK, and you’ll join a community of 13,000 international students.

1. MSc Data Sciences and Business Analytics at ESSEC Business School (France)

Finally, the best Masters in Data Science in Europe – the Data Science and Business Analytics programme at  ESSEC.  QS ranked this programme the best Master in business analytics in the world, and it’s easy to see why. The Master is a hybrid of data science, business analytics, and digital strategy and focuses on practical applications of skills. As a result, students can pursue technical roles in data analysis or opportunities in strategy and management.

Conclusions about the best masters in data science in Europe

Ten years ago, data science might have been a niche subject in a traditional business studies programme. Now, though, many universities across Europe offer dedicated Masters programmes in the subject. Whichever of these top Masters in Data Science programmes you choose, you’re sure to gain the skills and experience needed to undertake a career in the field. Good luck!

Editor’s note: This article was first published on the 26th of January 2022. We’ve updated it for current readers.

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