Alapadatok
Data Scientist
Department of Data Science and Engineering
Department of Programming Languages And Compilers
Department of Software Technology And Methodology
Department of Computer Algebra
Department of Algorithms And Their Applications
Department of Media & Educational Informatics
Department of Information Systems
Department of Numerical Analysis
Department of Cartography And Geoinformatics
Angol
Program
This program focuses on techniques to analyze large volumes of data and on information systems that use these techniques to offer smart services to their users. Graduates will be able to design and implement software solutions for supporting real-time data-driven decision making. Students will be familiarized with large scale and in-memory databases; the ecosystem of distributed processing and its components with particular focus on open-source development of these components; business analytics and reporting tools over aggregated data from multiple sources; visual analytics tools and their components; the utilization and adaptation of machine learning and data mining methods in realtime scenarios.
In 2016, the Data Science and Technology Department was established, with the support of T-Labs (Deutsche Telekom), as the first industrial department at ELTE. The department conducts a joint research program with Deutsche Telekom, involving students, company professionals, PhD students and lecturers of the University in its research activities. This program is recommended to applicants who:
want to understand the properties of various data types and the structure of complex data sets, recognize the relationships among data, apply the necessary raw data transformations, draw conclusions, and model real-world processes;
want to conduct analyses to detect, discover and better understand the abounding data around us generated by social media, manufacturing systems, medical devices, logistic services, and countless others, on a daily basis.
This program enables students to:
understand the concepts of data analysis, ethics, data security, mathematics, statistics, the programming principles and contexts – in particular, data types, representations, transformation and optimization procedures, as well as the principles of multivariate statistics and machine learning – which are required to innovate and conduct research in data science;
gain in-depth technical skills in scalable data collection techniques and data analysis methods, and learn how to use and develop a suite of tools and technologies that address data capture, processing, storage, transfer, analysis, visualization, and related concepts (e.g., data access, data pricing, and data privacy);
be aware of the operation of current technologies used for analysis and modelling, and be able to apply them in real-life situations, including the ones with large amounts of data;
be familiar with techniques used for storing, processing and visualizing large amounts of data, and with the properties of the different ecosystems of tools.
The high standard of training is guaranteed by the highly qualified academic staff. Teaching is supported by modern infrastructure and well-equipped computer labs (artificial intelligence, databases, and robotics). The library of the Faculty contains several thousand volumes. Upper-year students and PhD students help the first-year students in a mentoring system to overcome their first challenges at the university. In addition to the high level of theoretical training, the Faculty's relationship with the business community, the joint research and development projects offer up-to-date practical knowledge and experience to the students. The Faculty has concluded bilateral agreements with numerous universities in the world, which allows students to study one or two semesters, or participate in research projects, at a partner institution.
Extracurricular undergraduate research activities of the students are supported and supervised by leading scientists of the Faculty. These students present their findings at a conference organized by the Faculty every year. Workshops are also organized with international partners.
Felépítés
Karrier
Data science is a highly innovative area. Social media, manufacturing systems, medical devices, logistic services, and countless others generate petabytes of data on a daily basis. The data scientist simultaneously masters scalable data management, data analysis and domain area expertise to extract key knowledge and solve real-world problems.
- Data Scientist
- Data Analyst
Felvételi
Entry requirements
Holding a BSc degree in Computer Science or obtaining altogether at least 60 ECTS credits in informatics and mathematical subjects during a completed Bachelor's program related to Computer Science.
Language requirements
Minimum level of language proficiency (oral) (A1-C2): B2
Minimum level of language proficiency (written) (A1-C2): B2
Further comments: At least Intermediate level English language skills is required. English language exams are preferred (but not required) and any certificate is accepted.
| Document |
| Online application form |
| Secondary school certificate |
| Bachelor-level degree |
| Transcript of records |
| Proof of application fee transfer |
| CV |
| Motivation letter |
| Copy of the main pages of the passport (needs to be valid) |
| Passport photo |
| Language certificate |
The application starts in the online application system. Students need to register in the system, fill in the online application form, upload the required documents and follow the instructions during the application process.
The application fee should be paid using this Essential guide.
- Open the official payment platform of ELTE.
- Accept the privacy notices at the bottom of the page.
- Then click on Start Shopping.
- Select the Faculty (Faculty of Informatics) from the drop-down menu,
- then the payment title (application fee),
- then add the related study programme in the Subtitle section.
- Click on To the Cart.
- The cart summary will appear on the right-hand side of the screen. If you selected the right fee, click on Next.
- Fill out the Billing data.
- IMPORTANT!!! Fill in following Notice: MSc in Data Science, E10211/24
Without the correct comment, your payment will not be accepted! - then click on Go to Payment.
- Check your billing information; if everything is correct, click 'Pay'.
If you apply for several programs, you must pay the application fee for all applications. For each transfer, indicate the appropriate code and upload all bank slips.
Applications are only accepted being submitted through the online application system. Application materials sent via e-mail or by post are declined without further examination.
Entrance examination and selection process
In case of September intake: The applications are examined by the Admission Board until the end of May, applicants are notified of the outcome of the selection in the online application system until the middle of June.
Admission letters are sent out in the online application system until 30 June.
In case of February intake: The applications are examined by the Admission Board and are notified of the outcome of the selection in the online application system until the middle of November. Admission letters are sent out in the online application system until the end of November.
Applicants are required to participate in the online entrance exam and an online interview held and organized by the Admission Board of ELTE Faculty of Informatics in the first part of May (in case of February intake in the beginning of November).
Applicants are notified about
- time and date/duration of the entrance exam via e-mail one week before the starting date of the exam period by the programme coordinator,
- time and date of the online interview via e-mail 3 days before the online interview by the student coordinator.
Applicants can take the entrance exam and the online interview only one occassion. In case of communicational difficulties (weak network coverage) the student coordinator attempts to contact the applicant via e-mail and online platform twice within the deadline.
In case of lack of participation, posterial requests can not be accepted, appeals are declined after the deadline.
The program coordinator notifies all applicants about the outcome of the selection.
Type of entrance examination: oral and written
Place of entrance examination: online
Further details of the online interview:
The interview takes about 20 minutes in the previously indicated and scheduled time sent by the student coordinator via e-mail.
As the language of the education of the Computer Science Master course of ELTE Faculty of Informatics is English, applicants are required to possess at least intermediate level English language proficiency in order to take part efficiently of their academic studies. During the interview applicants are required to prove their English language and communicational skills by replying to questions about their previous studies, work experiences connected to Computer Science. Applicants are also required to answer simple questions concerning basic terms in mathematics and programming.
As the prerequisite of applying to Computer Science Master course is a previously obtained Bachelor degree in Computer Science or in a related field, no preparation is needed in advance, applicants are only have to be able to present their previously obtained skills.
Further details of the entrance exam:
In order to get admission to the Computer Science MSc programme applicants are required to participate and pass the online written entrance exam in Canvas system. Canvas is a learning management system used at Eötvös Loránd University. After accepting the invitation, previously sent by the programme coordinator, applicants are required to create a Canvas account. After logging in, exam exercises are available in Canvas system. There is no exact exam date, applicants are able to take the exam and submit their solutions whenever they want until the indicated deadline.
The exam consists of 1-3 programming problems. Solutions (program source codes in Java, C# or C/C++) are required to be submitted online.
Further details of selection and evaluation
The ranking is based on a total evaluation of the academic excellence (based on the submitted documents) and the results of the entrance exam.
Elérhetőségek
Mr. Zsolt BORSI
Assistant lecturer
E-mail: coordinator@csmsc.elte.hu
TEL: +36-1-372-2500/8494
Ms. Katalin SCHNEIDER
International coordinator
E-mail: katalin.schneider@inf.elte.hu
TEL: +36 (1) 372 2500 / 8138
Dr János Botzheim
Associate Professor
Find the stucture of the program on this link.