Master’s programme in Big Data & Data Science
Big data refers to the massive amounts of information becoming available as people use the internet and computers more
This data can generate powerful insights in domains ranging from business and entertainment to politics and healthcare
However, the amount of data being captured today is ever-increasing and extends beyond the storage and analyzing capacity of traditional applications
WHY BIG DATA & DATA SCIENCE?
The amount of data being captured today is ever-increasing and extends beyond the storage and analyzing capacity of traditional applications.
With us you will learn how to get the information you need out of an array of multidimensional, heterogeneous, incomplete, inaccurate, and inconsistent data and do it effectively.
Big data refers to the massive amounts of information becoming available as people use the internet and computers more. This data can generate powerful insights in domains ranging from business and entertainment to politics and healthcare. However, the amount of data being captured today is ever-increasing and extends beyond the storage and analyzing capacity of traditional applications.
This Master program is aimed at training specialists in the field of Big Data and Data Science.
Data Science is a rapidly growing field and job market. Successful career in data science starts with obtaining a solid knowledge and skill base, that can be offered by a combination of classic education and modern practically oriented interactive learning. If you want to start you career path in the exciting new area the right way – you can join our course. Upon the completion of our program you’ll be able to choose the best application for your skills in research, business, analytics or technical area.
The program Big Data & Data Science includes various branches of data analysis and machine learning and has three academic tracks («Industry 4.0», «Bioinformatics and Biomedicine», «Social Media»).
Program in English.
- Digital Signal Processing
- High Performance Computing
- Research Topics in Industry 4.0 (Industrial Data Analysis)
- Research Topics in Industry 4.0 (VR/AR technologies)
- Research Topics in Industry 4.0 (Digital Image and Video Processing)
- Fundamentals of Molecular Spectroscopy
- Modeling of molecular targets for medical diagnostics and therapy
- Research Topics in bioinformatics
- Research Topics in biomedicine
- Social Network Analysis 1
- Data mining in Social Media 1
- Research Topics in Social Media : Methodology of Social Media research
- Research Topics in Social Media : Preparation of research tools
July 10, 2017 on the basis of the Faculty of Informatics and the Faculty of Applied Mathematics and Cybernetics of TSU, the Institute of Applied Mathematics and Computer Science (IPMC) was formed. The Faculty of Applied Mathematics as a structural subdivision of TSU was established on July 3, 1970. In the early 1980's it was renamed to the Faculty of Applied Mathematics and Cybernetics. In 1986 the Faculty of Informatics was formed as an educational and scientific complex "Informatics" on the basis of the Department of Programming and Informatics, the Department of Economic Cybernetics, the Laboratory of Computing Systems, and the Computing Center of TSU, in 1992 it was reorganized into the Informatics Department.
The staff of the Institute are 114 teachers, including 31 Professors and 55 associate professors.
Institute staff carry on active research.The main areas of researchin the field of Big Data& Data Science aredevelopment of theoretical and technological fundamentals of artificial intelligence, big data preprocessing and analysis methods and models, machine learning and semantic data systems methods and models, pattern recognition and classification, technologies for automated detection and classification of ground and overwater objects using statistical and neural network algorithms.
Admission and application
Required documents (to be submitted online):
1) a passport copy;
2) a diploma copy (OR a registrar-issued transcript of grades for the last semester); upon arrival students must provide the admissions committee with an original document;
NOTE! documents received in a foreign country are submitted legalized in accordance with the procedure established by the legislation of the Russian Federation, or with the apostille (except when, in accordance with legislation of the Russian Federation and (or) an international treaty legalization and apostille are not required)
3) certified translation of the diploma and the passport into Russian language (can be submitted upon the arrival)
4) a completed application form (online)
5) other diplomas and certificates proving any other achievements (if available)
6) motivation letter
7) entrance exams:
– an interview
Cost and Fundings
|Year||Citizens of the Russian Federation and near abroad||Other International Citizens|
|2020-2021||request information||request information|
Scholarships are available via the Russian government scheme.
To participate in the interview, please fill out a registration form on the program website: http://cs.tsu.ru
Application deadlines for the citizens of the Russian Federation and near abroad in 2020 year
|Application deadline||request information|
|Entry exams||request information|
Application deadlines for the other International citizens in
|Application deadline for international students||request information|
|Entry exams for international students||request information|
Graduates of the programme will have a unique combination of skills in data science and data management.
tour graduates are able to process and manage data effectively and efficiently, extract value from data, to visualise it and to communicate it.
The programme serves increasing demands from industry which relies upon massive volumes of data.
Russian and international companies such as IBM, Infosys, Oracle and Orion increasingly need specialists in this field.
Median Salaries for Jobs Related to Data Science (Source: www.payscale.com)
Apply Right Now!
To know more about the programme Big Data & Data Science, please contact:
Olga Marukhina (program manager)
Academic office: TSU Building № 2, office 038