The program is aimed at training highly qualified specialists in the field of digital business and artificial intelligence. Students will gain in-depth knowledge in the field of digital business, data analysis, machine learning and the development of innovative products based on artificial intelligence. The program combines theoretical knowledge and practical skills, enabling graduates to successfully apply their acquired knowledge in a rapidly changing digital environment. Graduates of the program are in demand in various fields, including IT companies, consulting, finance, and IT and AI startups.. Methods of conducting scientific research on digital business issues are also being studied, including the use of AI technologies to analyze processes and projects using databases and knowledge banks.
Admission Committee
(7172) 64-57-10
info@astanait.edu.kz
Mon-Fri 9:00 – 18:00
Training of highly qualified specialists in the field of business analytics, innovation management and artificial intelligence within the framework of an interdisciplinary educational program combining elements of management, digital technologies and data analytics. Graduates will be able to effectively apply modern management and technological solutions in international and domestic companies, start-ups, consulting structures and research organizations using AI technologies.
The aim of the course is to develop professional competences of specialists; to form professionally oriented communicative competence of master’s students, which allows them to integrate into international professional environment and use professional English as a means of intercultural and professional communication.
The content of the course is aimed at the formation of systemic ideas about the psychological laws of management, the specifics of using social and psychological knowledge and mastering the skills of analyzing the social and psychological principles that underlie effective management.
The content of the course is aimed at obtaining knowledge about the properties of science as a type of cognition and a socio-cultural phenomenon in its historical development by a master student; formation of system ideas about the general laws of scientific knowledge in its historical development and changing socio-cultural context.
The content of the course is aimed at acquiring knowledge about the foundations of pedagogical theory and pedagogical skills, the management of the educational process for teaching in higher education, the formation of an understanding of the main categories of pedagogy, the place, role and significance of higher education pedagogy, understanding the basic principles of modern pedagogy and methodological approaches to solving pedagogical problems of higher education.
Teaching practice is a kind of practical activities of graduate students, including teaching, organization of educational activity of students, scientific and methodical work on the subject, obtaining skills in teacher’s work.
The course is aimed at an in-depth study of modern AI methods, including deep learning, neural network architectures, enhanced learning and generative models. Special attention is paid to the practical application of algorithms and working with TensorFlow and PyTorch libraries in real-world tasks.
The aim of the AI Applications and Impacts course is to provide students with a deep understanding of the practical applications of artificial intelligence in various industries and to assess its social and ethical impact. Students study real-world examples of AI applications such as computer vision, natural language processing, recommendation systems, and autonomous systems. The course will also cover ethics issues related to the use of AI, including issues of data bias, privacy, and the responsibility of algorithms.
The course is aimed at developing students’ systems thinking, allowing them to analyze the current state of the business, identify areas for improvement and develop digital transformation strategies.
• Analyze the current state of the business and identify areas for improvement through digital technology.
• Develop digital transformation strategies that meet business objectives.
The purpose of the Machine Learning for Business course is to train specialists who are able to apply machine learning methods to solve real business problems. Students will study basic machine learning algorithms, learn how to develop and train models, and apply them to predict, classify, and cluster data. The course focuses on practical aspects of applying machine learning in business, such as analyzing customer behavior, optimizing marketing campaigns, predicting sales, and detecting fraudulent activity.
The discipline is aimed at developing graduate students a broad understanding of research methodology, critical reading skills of scientific literature and development of research tools.
Within the discipline, undergraduates are offered a variety of strategies and tools to create an interactive and stimulating learning environment. During the course, students learn various active methods such as group projects, role-playing games, feedback and discussions, the use of technologies and tools for interactive learning and ways to adapt them to the specifics of IT disciplines and integrate practical tasks and projects into the learning process.
This module is designed to strengthen students ” research and cross-cutting skills, especially in relation to research and communication in an English language environment. The courses cover several areas of scientific skills, including scientific communication and presentation skills, theory of science, scientific methodology, and teamwork skills.
Students will learn modern methods of collecting, storing, and processing big data, master tools and technologies for data analysis, and learn how to build predictive models and visualize analysis results. The course aims to develop analytical thinking and data-driven decision-making skills, which are key requirements for successful work in the digital economy. They will learn how to work effectively with large amounts of data, extract valuable information from them and apply the knowledge gained to make informed business decisions.
This module is designed to strengthen students ” research and cross-cutting skills, especially in relation to research and communication in an English language environment. The courses cover several areas of scientific skills, including scientific communication and presentation skills, theory of science, scientific methodology, and teamwork skills.
The course is aimed at developing students’ managerial competencies in the field of business process optimization, operational planning and logistics using artificial intelligence technologies. The discipline examines the application of machine learning to predict demand, manage inventory, plan resources, and improve supply chain efficiency. Special attention is paid to the development and implementation of intelligent management solutions based on real-time data analysis.
The course aims to explore the strategic use of artificial intelligence (AI) and business analytics to increase the competitiveness of companies. Students master the techniques of data analysis, forecasting, decision automation, and developing AI strategies for businesses.
The course is aimed at training specialists capable of integrating blockchain and artificial intelligence to create innovative solutions in the field of digital business. Students will learn the principles of blockchain, its application in various industries, as well as ways to combine blockchain with machine learning algorithms to improve the security, transparency, and efficiency of business processes.
The course examines cutting-edge innovations in the field of artificial intelligence (AI) and their role in the development of entrepreneurship. Students will get acquainted with key technologies, strategies for creating AI startups, business models and mechanisms for attracting investments. The course combines theoretical knowledge, analysis of successful cases and practical work on their own projects, they will be able to develop innovative AI solutions, build sustainable business models, attract investments and manage AI startups.
This course aims to provide students with a holistic understanding of the interrelationship of ethical, legal and technological aspects of the development and implementation of artificial intelligence systems in the context of digital transformation. Within the framework of the module, they master methods for ensuring the protection of information systems using modern machine learning and deep learning algorithms. Special attention is paid to threat intelligence technologies, detection and prevention of cyber attacks, as well as the design of adaptive security systems capable of functioning effectively in the face of evolving cyber threats. The second part of the course covers key issues of ethics and government regulation in the field of AI. It examines fundamental ethical principles, including fairness, transparency, accountability, and non-discrimination, and analyzes the potential social consequences of widespread AI adoption. Modern regulatory approaches to AI regulation at both national and international levels are considered. The course develops the ability for critical thinking, interdisciplinary analysis and informed decision-making in the field of responsible and safe use of artificial intelligence technologies.
The purpose of the NIRM is to develop the ability to independently perform research work related to solving professional tasks necessary in the further scientific and professional activities of master managers and master marketers. NIRM helps to systematize, consolidate and expand theoretical knowledge, develop statistical methods in project management, master the elements of independent research work.
The thesis is a written scholarship work in which it must be documented that the candidate is independently able to apply scientific and practical methods to handle complex tasks taken from certain subject areas, including not only specific individual technical details, but also broader implications. The dissertation combines the competencies obtained as a result of research and applies them to the topic of the dissertation preferred in the same company as the case study and the project. It provides scientific analysis and analysis covering the entire spectrum of the educational program and the corresponding scientific problem.
basic courses in artificial intelligence as part of Stage 0 of the AI-Sana innovation program.
course is “Artificial Intelligence Technology and Applications” on the Huawei, MIT, Google, Microsoft platform.