Algorithms and systems for big data processing Master specialty comprises the training of high professional qualification specialists focused on interdisciplinary research in the development and research of mathematical models in information systems and distributed heavily loaded networks, as well as specializing in the development of efficient algorithms (parallel, approximate) processing of large volumes of information, on the analysis and searching for dependencies stored in distributed data cluster and cloud systems. The current level of training of specialists in this master's program provides a good knowledge of basic concepts and methods of mathematical modelling in a concrete subject area, as well as fluency in the latest instrumental methods and tools of complex information systems development. Master's graduates work for companies whose activities are related to the development of highly services on the Internet, the creation of knowledge-based innovation systems used in commerce, industry and other fields. Academic plan of the specialty: | List of academic disciplines | Total hours | Classroom hours | 1 | Modern methods of designing effective large amounts of data processing algorithms | 172 | 68 | 2 | Technology and computer systems processing large volumes of data | 172 | 68 | 3 | UNIX family Operating Systems | 188 | 68 | 4 | Script programming language (Python) | 112 | 54 | 5 | Technology design and development of high-oaded web-based systems | 112 | 54 | 6 | Word processing algorithms | 170 | 66 | 7 | Elective courses: Introduction to Machine Learning / Introduction to Information Retrieval / Introduction to linguistics and automatic text processing | 112 | 54 | | Preparation of Master's thesis | 744 | | | Practice | 162 | | In the 2016-2017 academic year, it is planned to establish a plan of admission to the budget form of training - 20 students on a paid form - 10 students. The Master’s Degree Program requires the first stage of higher education students in the following directions: | Mathematical Sciences and Computer Science (code 1-31 03) | | Computer Science and Engineering (code 1-40) |
|