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Data and Applications Integration Technology

Master's Degree, Institute of High Technology and Piezo Engineering

09.04.03 Applied Informatics ​​​​​​​

Program length: 2 years

Language of study: Russian

Place of study: Rostov-on-Don

Purpose of this educational program:

The program is aimed at students with a basic level of knowledge and is implemented to study data processing and integration technologies. A set of problems related to information exchange between enterprises or between software products of different manufacturers and different target applications used within the same enterprise are traditionally solved by using integration tools.

The problem of data integration is also acute in the field of machine learning, computer vision, and working with big data. Thus, integration technologies cover all levels of information systems architecture, which determines the focus of the program - training IT-specialists skilled in modern technologies of data processing and integration and capable of solving business problems by applying modern principles of organizing interaction of cross-platform software products.


Core curriculum:

Basis

Specialized subjects

 Methodology of scientific work

Application-data integration toolkit

Research project

Machine learning technology

IT-projects management

Computer vision technology

IT software and hardware

Extracting and constructing classification attributes of information system models

Intelligent analysis methods in information systems

Integration of IT into information systems and services


Data base models

Among the advantages of this study program are:

  1. The program is implemented in Rostov-on-Don and there is an opportunity to study in parallel under the military training program - reserve officer (http://ivo.sfedu.ru/abiturientu/perechen-napravlenij-podgotovki-dlya-obucheniya-v-vucz-2020-2021).
  2. Modern comfortable dormitory (Southern Federal University campus, Rostov-on-Don, Zorge Street 21 (https://yandex.ru/images/search?text=%D1%8E%D1%84%D1%83%20%D0%BA%D0%B0%D0%BC%D0%BF%D1%83%D1%81%20%D0%B7%D0%BE%D1%80%D0%B )
  3. Rapid practical immersion and career guidance in solving a variety of practical problems, both research problems solved at the Neurotechnology Research and Development Centre, and business problems formulated by the program partner - regional leading enterprise "Soyuz Company", as well as the Russian scale company LLC "Analytical Centre for Sustainable Development and Digital Economy" (Moscow). The large variety of applied tools for problem solving makes the threshold for entering the field of professional activity very high. All students take part in the Artificial Intelligence federal competition held by Samsung Research Centre.
  4. Upon successful completion of the final work of the Samsung Academy IoT course, the student receives an internationally recognized certificate of study endorsed by Samsung.


Prospects. Career & Employment

Graduates are in high demand in today's job market and have many offers. For example, Position: Data Scientist/Analyst Knowledge: Python; Knowledge of statistics (regression, decision trees, clustering, etc); Additional programming language Java; Experience in SQL. Position: Data Engineer. Knowledge of: Experience in ETL-processes design and development (uploading, transformation and loading data from different sources); Experience in Big Data: Hadoop, MapReduce, Spark & Spark Streaming, Hive, Kafka, SQL. Position: DL Engineer Knowledge of: Python; Pytorch/Tensorflow; Java; Read and understand articles; Take research results and adapt them for your company; Accelerate algorithms; Backend developer + ML Skills. Position: DL/ML Researcher Knowledge of: Python; Pytorch/Tensorflow; Math: Calculus, Linear Algebra, Probability Theory, Ma-chine Learning Theory, Probabilistic Graphical Models; Implement DL algorithms and adapt them for the right domain.


Student achievements

  1. Winners of Samsung's national student paper competition (https://myitacademy.ru/o-konkurse/)
  2. Recipients of personalised scholarships
  3. Publications in Scopus, Web of Science