8D06101 Clever Systems
Educational Program Description

In the modern world of information technology, there is a fundamentally new qualitative shift that radically changes the markets and the environment in which we live and work every day. This is primarily due to the penetration of digital technologies into the daily life of people and companies that have become “digital”. Indeed, after digitizing every bit of data and getting rid of paper media, the global business landscape has become a network with close internal connections.

According to a study by the international research and consulting company International Data Corporation (IDC), almost half of the companies declared their "digital aspiration". This means that people are required to be ready to develop digital strategies and architectures that mimic the work of companies that originally built their business around digital technologies. A workforce leveraging cloud, Agile and DevOps practices, digital innovation platforms and communities, and integrated data management and monetization.

The digital system is a metaphor that suggests considering modern organizations as mixed communities and systems in which people and digital agents interact. At the same time, openness in combining the efforts of developers, developing public-private partnerships and building a competitive environment in order to ensure a rapid growth in the number of available digital services, as well as improve their quality.

Analyzing reports and research, analytical companies IDC, Deloitte Consulting, Accenture, having studied the educational programs of leading IT universities in the UK, USA, Canada, etc., it can be concluded that it is necessary to train specialists with the knowledge and skills of creating intelligent ecosystems.

Intelligent ecosystems automate work tasks and create intelligent environments; they force machines to communicate with each other - for example, in mobile payments, healthcare, traffic, security or surveillance, etc. In this educational program, students will learn how to map needs and design and implement solutions for consumer technologies such like beacons, mobile phones, smart cities and homes. Will explore an introduction to machine technology, digital systems, automation and control, programming, networking, the Internet of Things and sensor networks. Achieving this qualification requires knowledge of design processes, sensors, tools, and technology. Intelligent systems provide the necessary tools and knowledge, including a detailed introduction to sensors, networks, design and implementation. In addition, the ability to plan, develop and implement projects of intelligent information systems and the Internet of Things.

The PhD doctoral level study program is a coeducation for all IT programs and provides professional qualifications

  • in the field of knowledge representation and processing in intelligent systems,
  • in the field of studying methods for constructing logical, production, network models and their use in intelligent systems for various purposes: expert systems, fuzzy systems, decision support systems, neural network and genetic algorithms.
  • developing methods for solving problems for which there are no formal algorithms: understanding natural language, teaching, proving theorems, recognizing complex patterns, etc.

Theoretical research is aimed at studying intellectual processes and creating appropriate mathematical models. Experimental work is carried out by compiling computer programs and creating machines that solve particular intellectual problems or behave reasonably in a given situation.

The educational program will contribute to the formation of the student's abilities and skills in the areas of solving design and management problems based on artificial intelligence methods, green technologies, software development for modern intelligent ecosystems.

Objectives of the educational program

Purpose (goals) of mastering the discipline:

Training of competent research and teaching personnel to meet the needs of science, education and production in the field of modern intelligent ecosystems.


  • study of the principles of organization of modern intelligent systems;
  • mastering the methods of knowledge representation and inference methods in modern intelligent systems;
  • study of methods and software for the development of intelligent systems for various purposes;
  • analysis of real problems, the use of intelligent systems for solving problems by means of expert systems, decision support systems.

The purpose of the EP is to prepare a universal specialist who has knowledge in mathematics, statistics, ICT, computer science, business

Objectives of the OP:

  • familiarization with the concepts and methods that form the basis for understanding the current advances in artificial intelligence and ecosystems;
  • presentation of the technical formulation of the main tasks solved by artificial intelligence systems;
  • determining the value of a software product through integration with other products
  • familiarization with modern areas of research in artificial intelligence;
  • familiarization with the basic models of knowledge representation and some intelligent systems;
  • consideration of theoretical and some practical issues of the creation and operation of expert systems, systems;
  • familiarization with the features of the practical use of intelligent information systems and decision-making systems.
  • consideration of a set of services, devices, and other products of one company inextricably linked into a single network;
  • development of intelligent information systems or knowledge-based systems.
  • the student must have the skills of complex analysis and analytical generalization of the results of research works using modern achievements of science and technology, the skills of self-collecting data, studying, analyzing and summarizing scientific and technical information on the research topic, the ability to create theoretical models that allow predicting the properties of the objects under study and develop proposals for the implementation of the results.
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