Education levelBachelor
Passing score (paid education)90
FacultyInformation Technology and Artificial Intelligence
ID1940
About the program
The purpose of the educational program "6B06106 - Highly loaded information systems with artificial intelligence" is to train highly qualified specialists who are able to design and develop high-loaded systems with artificial intelligence for processing large amounts of data using data pipeline processing tools and parallelizing computing processes between different domains based on Akka technology, highly erudite professionals with high ethical standards of behavior in society, able to improve their level of education throughout their lives.
Graduate model
1.Demonstrate knowledge about models, structures, algorithms of modern programming languages, models, structures, algorithms of artificial intelligence technology, technologies of design, deployment and integration of corporate systems
2.Interpret the knowledge gained in substantiating the architecture, model, composition of the software product, their functional purposes, choice of programming language, design technology, composition and purpose of services, ways to implement the business logic of the project, principles of flexible programming, standards of industrial development
3.To argue the principles and methods of applied areas of network technology, the composition and purpose of clusters, the degree of solidity and microservice architecture, the choice of technology and design methods, the choice of a web application platform, the principles of using APIs, artificial intelligence, network technologies, containerization technology and application orchestration
4.Demonstrate knowledge of specialized software and hardware systems for solving problems of data analysis, processing, reception and transmission of results, storage and effective management methods, the task of creating secure data warehouses, increasing productivity, reliability and safety of use, problems of noise immunity and validity of solutions, relevance and reliability of data and solutions
5.Substantiate the theoretical foundations of asynchrony and parallelism of methods, methods of using RAM, reflection and caching, artificial intelligence, CI\CD technology, scaling technology, malware protection technology, management and design principles, integration platforms and module connectivity, flexibility and responsiveness of the application.
6.Discuss and integrate interdisciplinary knowledge in solving management and planning tasks, production adequacy tasks, cost-effectiveness justification tasks, technological process modeling tasks, justification and economic feasibility tasks, technical and technological adequacy, distribution tasks, separate accounting, energy intensity tasks, environmental safety, labor protection
7.Apply the basic methods, approaches and techniques of programming languages, artificial intelligence, network programming, technologies for storing, managing and receiving/transmitting information, microservice architecture, reactive functional programming, continuous integration technologies, containerization and orchestration, testing technologies, product protection and security, distributed systems, cloud technologies.
8.Use methods of modeling technological processes, phenomena and processes of phenomena, their interrelations for adequate reproduction of processes and phenomena, as well as establishing their cause-and-effect relationships, to ensure the relevance and reliability of data, the truth and adequacy of data, accessibility and timeliness, for the reliability and reproducibility of data, the ability to argue for ways of data delivery
9.Analyze and argue technological and technical problems related to the development of risks of inappropriate behavior of the software product, model, functional relationships, structure and methods used, cluster technology in this environment, software product platforms, design decisions made, dynamic relationships used, libraries, instructions of the adopted scenario algorithm
10.Use the materials of the provided training courses and analyze the information obtained to make forecasts of the behavior of the software product, individual modules, methods and tools used, the behavior of the customer's software environment, network equipment, communication equipment, information system development, technologies used, platforms, libraries, programming languages
11.To make forecasts of the manifestation and development of artificial intelligence technology using modern innovative methods for making managerial decisions to improve the functional properties of the product, its reliability, productivity, flexibility, responsiveness, to form the basic foundations of the designed product, writing basic services, program architecture, to improve the efficiency of the programmer, the team as a whole, architectural solutions, flexibility and modernity
12.Formulate their own judgments containing scientific positions on the behavior of the constructed system, model, module states, embedded dependencies and relationships, reproducibility of the studied effect, data sources, mechanisms for the formation of features of the context of the technological chain of judgments, the mechanism of transformation of contextual information during the transition from one layer to another neural networks
2.Interpret the knowledge gained in substantiating the architecture, model, composition of the software product, their functional purposes, choice of programming language, design technology, composition and purpose of services, ways to implement the business logic of the project, principles of flexible programming, standards of industrial development
3.To argue the principles and methods of applied areas of network technology, the composition and purpose of clusters, the degree of solidity and microservice architecture, the choice of technology and design methods, the choice of a web application platform, the principles of using APIs, artificial intelligence, network technologies, containerization technology and application orchestration
4.Demonstrate knowledge of specialized software and hardware systems for solving problems of data analysis, processing, reception and transmission of results, storage and effective management methods, the task of creating secure data warehouses, increasing productivity, reliability and safety of use, problems of noise immunity and validity of solutions, relevance and reliability of data and solutions
5.Substantiate the theoretical foundations of asynchrony and parallelism of methods, methods of using RAM, reflection and caching, artificial intelligence, CI\CD technology, scaling technology, malware protection technology, management and design principles, integration platforms and module connectivity, flexibility and responsiveness of the application.
6.Discuss and integrate interdisciplinary knowledge in solving management and planning tasks, production adequacy tasks, cost-effectiveness justification tasks, technological process modeling tasks, justification and economic feasibility tasks, technical and technological adequacy, distribution tasks, separate accounting, energy intensity tasks, environmental safety, labor protection
7.Apply the basic methods, approaches and techniques of programming languages, artificial intelligence, network programming, technologies for storing, managing and receiving/transmitting information, microservice architecture, reactive functional programming, continuous integration technologies, containerization and orchestration, testing technologies, product protection and security, distributed systems, cloud technologies.
8.Use methods of modeling technological processes, phenomena and processes of phenomena, their interrelations for adequate reproduction of processes and phenomena, as well as establishing their cause-and-effect relationships, to ensure the relevance and reliability of data, the truth and adequacy of data, accessibility and timeliness, for the reliability and reproducibility of data, the ability to argue for ways of data delivery
9.Analyze and argue technological and technical problems related to the development of risks of inappropriate behavior of the software product, model, functional relationships, structure and methods used, cluster technology in this environment, software product platforms, design decisions made, dynamic relationships used, libraries, instructions of the adopted scenario algorithm
10.Use the materials of the provided training courses and analyze the information obtained to make forecasts of the behavior of the software product, individual modules, methods and tools used, the behavior of the customer's software environment, network equipment, communication equipment, information system development, technologies used, platforms, libraries, programming languages
11.To make forecasts of the manifestation and development of artificial intelligence technology using modern innovative methods for making managerial decisions to improve the functional properties of the product, its reliability, productivity, flexibility, responsiveness, to form the basic foundations of the designed product, writing basic services, program architecture, to improve the efficiency of the programmer, the team as a whole, architectural solutions, flexibility and modernity
12.Formulate their own judgments containing scientific positions on the behavior of the constructed system, model, module states, embedded dependencies and relationships, reproducibility of the studied effect, data sources, mechanisms for the formation of features of the context of the technological chain of judgments, the mechanism of transformation of contextual information during the transition from one layer to another neural networks
Contacts
Al-Farabi Kazakh National University Republic of Kazakhstan, Almaty, 050040, 71/23 Al-Farabi Ave. Faculty of Information Technologies and Artificial Intelligence
Head of the Department, Acting Associate Professor Shormakova Assem
Deputy Head of the Department for Academic, Methodological and Educational Work, Senior Lecturer Ilessova Bakhytgul
Deputy Head of the Department for Research, Innovation and International Relations, Senior Lecturer Duisenbekkyzy Zhansaya
Admission
1) Certificate/diploma+appendices(original)
2) Identity card(original and 2 copies)
3) UNT certificate(certificate.testcenter.kz)
4) Documents confirming benefits/quotas(original and copy)
5) 3x4 photos 6pcs.
6) Medical certificate 063/y(copy), 075/y
7) Language Certificate
8) Extract from the statement of the creative/ special exam(if available)
9) Grant award certificate(grant.testcenter.kz )
10) Receipt confirming payment of 50% of tuition fees(for paid tuition)