• Scientific and pedagogical direction - Master of Engineering Sciences

ON 1 to Use the conceptual apparatus, methods, techniques and technologies for the development and optimization of data collection tools (data mining) based on the analysis and synthesis of information data flows characteristic of the banking sector, Internet Commerce, IoT, social networks, data measuring devices of complex technical objects(TO), DC servers;
ON 2 to Carry out comparative–regression, comparative-probabilistic, system and structural analysis for modeling and formalization of large information data flows of the Internet space;
ON 3 Solve network technical, economic-marketing, banking, information and forecast - extrapolation problems based on the analysis of information with a large amount of data to structure this information into a single, understandable and formalized mathematical model;
ON 4 Process server data, THEN, Internet sources using methods of mathematical statistics and new information technology, computer technology using modern hardware and software Hadoop & MapReduce;NoSQL database
Data Discovery class tools;
ON 5 to Correlate methodological foundations of mathematics, control and decision-making theory, Informatics, information security systems, to distinguish between discussion concepts and paradigms widely discussed in the modern foreign and domestic scientific and technical environment;
ON 6 Effectively generate analytical reviews and generate accurate forecasts for management decision-making based on dynamic, structured and processed sources of diverse DC information, Internet resources, the readings of numerous sensors of complex;
ON 7 Create new knowledge bases and segments in the DC. To design pilot Big Data Analytics for MAINTENANCE and business processes with the formation of mathematical models for processing large data flows of al Farabi KazNU;
ON 8 Create projects on GeoJinni (new version of SpatialHadoop) that allows you to add geospatial functions to various hadoop layers and components for storing, processing, and indexing large GEODATA;
ON 9 to Form pilot courses for training of employees of business companies, to conduct trainings on big data, machine learning and development of interfaces. Be able to present the conceptual apparatus ML/AI/Big Data and their applications transparently and clearly;
ON 10 Have the skills to use Oracle package programs to process data of specific big Data sources in context search and storage of data on servers;
ON 11 Apply Big Data analyst methods to study the relevant needs of customer groups of business processes to determine the non-selling and most marginal groups of services and products;
ON 12 to Use skills of work with information from various literary sources, to represent it in various forms of messages, presentations and reports taking into account specifics of audience, justifying and competently expressing the point of view on problem questions. Work effectively as a team in the search and solution of research problems of OP.