7M06102 · MASTER’S · PROFESSIONAL
AI+X, professional master’s
A faster route into industrial AI: the same engineering competencies as in the two-year version, but in one year and without the research and teaching track.
1 year
DURATION
60 credits
PROGRAM WORKLOADWORKLOAD
Russian and English
LANGUAGE OF INSTRUCTIONLANGUAGE
Full-time
MODE OF STUDYMODE
Master of Engineering and Technology
DEGREE
3 000 000 ₸ per year
TUITION
Fee-paying only
FUNDING BASISBASIS
24 July — 28 August
ADMISSION 2026–2027
ABOUT THE PROGRAM
This is the professional (practice-oriented) version of the AI+X master’s program — for those who want engineering competencies in industrial artificial intelligence sooner, without the research and teaching track, but with the same focus on industry.
The program trains management and engineering professionals for the sectors of the economy, with advanced professional knowledge and competencies in making digital and production systems intelligent, in analyzing and processing data, in deploying AI systems in the corporate and industrial environment, and in optimizing technological processes. The program is aimed at solving practical and industrial tasks in developing, deploying and applying artificial intelligence technologies.
CAREER
What graduates do
- Artificial intelligence engineer
- AI systems architect
- Head of a structural unit
The same range of career positions as in the two-year version, but with a faster entry into the labor market.
INDUSTRIES
FEATURES
Program features
A shorter format without losing engineering depth
Just 1 year and 60 credits — the program gives full engineering and management competencies in a short time, for those who want to reach a new professional level in industrial AI quickly.
The degree of Master of Engineering and Technology
The degree awarded reflects the engineering, practical nature of the training directly — unlike the degree of Master of Technical Sciences in the research and teaching version of the program.
A practical focus rather than a research one
Instead of a master’s thesis there is a master’s project; the program ends with industrial practice and the defense of that project.
The full AI+X engineering stack in a compact format
AI systems architecture and MLOps, the integration and deployment of AI systems, advanced machine learning, generative AI — the same industrial stack as in the two-year version.
AI security as a professional field of its own
AI Security and Risk Analysis stays in the program even in the compact format — security and risk are not sacrificed to the speed of study.
A flexible track with two directions
Industrial AI and Smart Systems and AI Systems Engineering and Security — the same choice of specialization as in the two-year program.
The same set of career opportunities in less time
From artificial intelligence engineer to AI systems architect and head of a structural unit — with a faster entry into the labor market.
SPECIALIZATIONS
Educational tracks
The program runs along two learning tracks, aimed at optimizing production processes and at building scalable AI systems.
Industrial AI and Smart Systems
A track for those who want to apply artificial intelligence to optimizing industrial processes and to production diagnostics. It covers industrial AI and predictive diagnostics, IoT and Edge AI in industry.
AI Systems Engineering and Security
A track for those who want to design scalable and secure AI systems: AI systems architecture and MLOps, the integration and deployment of AI systems, advanced machine learning, AI security and risk analysis, building products on generative AI.
A track is chosen according to the student’s professional interests and is supported by elective courses and project work.
LEARNING OUTCOMES
What you will learn
On completing the program, a graduate is able to:
- Build AI solutions that raise the effectiveness of organizations and production systems amid digital and industrial transformation, and make management decisions based on data.
- Apply methods of collecting, storing, processing and analyzing data and use analytical tools and visualization technologies to solve complex technical and applied tasks.
- Apply machine learning and artificial intelligence methods, design, train, test and optimize AI models, and evaluate their effectiveness.
- Design the architecture of AI systems, apply data engineering methods, build high-load and scalable intelligent systems and integrate them into corporate infrastructure.
- Deploy AI models into the production environment, use MLOps tools, manage the lifecycle of models, monitor them and ensure the reliability of intelligent systems.
- Apply AI technologies to optimize production processes, energy systems, IoT infrastructure and smart manufacturing environments.
- Design distributed and cloud AI systems, manage data infrastructure and deliver intelligent solutions in high-load computing environments.
- Build digital products on generative AI, define what they do, create prototypes and bring AI solutions into practical use.
- Ensure data security, assess risks, meet cybersecurity requirements and keep intelligent systems resilient when building and deploying AI solutions.
- Carry out applied research in business analytics and artificial intelligence, analyze and interpret the results, and prepare analytical reports and technical documentation.
PRACTICE AND TOOLS
Practice and tools
During their studies students gain hands-on experience of building, deploying and managing AI systems at industrial scale.
- Designing the architecture of AI systems
- High-load and scalable intelligent systems, integration into corporate infrastructure
- MLOps and model lifecycle management
- Deploying AI models into the production environment, monitoring, ensuring reliability
- Industrial AI and predictive diagnostics
- Applying AI technologies to optimize production processes, energy systems and IoT infrastructure
- Distributed and cloud AI systems
- Managing data infrastructure, delivering solutions in high-load computing environments
- Generative AI
- Building digital products on generative AI, creating prototypes and bringing solutions into practical use
- Security and resilience of AI systems
- Assessing risks and meeting cybersecurity requirements when building and deploying AI solutions
- Industrial practice
- Real experience of working in an organization, applying the competencies gained
The program ends with industrial practice and the defense of a master’s project — an applied rather than a theoretical result of study, confirming that the student can design and deploy a working AI solution on their own.
STUDY PLAN
What you study
Courses marked “Elective” are chosen by the student.
| Course Title | Credits |
|---|---|
| FUNDAMENTAL DISCIPLINES | |
| Psychology of Management | 3 |
| Foreign language (professional) | 3 |
| Elective: AI for Industrial Process Optimization and Control / AI Systems Architecture and MLOps | 4 |
| MAJOR DISCIPLINES | |
| AI Security and Risk Analysis | 5 |
| Generative AI Product Development | 5 |
| Industrial practice | 4 |
| Elective: Industrial Artificial Intelligence and Predictive Diagnostics / Advanced Machine Learning for AI Systems | 5 |
| Elective: Digital Twins and Intelligent Infrastructure Systems / Advanced MLOps and AI Lifecycle Management | 5 |
| Elective: IoT and Edge AI in Industry / AI Systems Integration and Deployment | 5 |
| EXPERIMENTAL AND RESEARCH WORK AND CERTIFICATION | |
| Experimental and research work of a master’s student, including an internship and a master’s project | 13 |
| Design and protection of the master’s project | 8 |
TUITION AND FUNDING
Tuition
STUDY
3 000 000 ₸
per year, professional master’s, full-time. Payment terms are set by the contract.
SUBMIT DOCUMENTS — Opens in a new tabSTATE GRANTS
Not available for master’s programs
Admission to a master’s program runs on a fee-paying basis only — by competition on the results of the Comprehensive Test (CT).
ADMISSION
How to apply
Take the Comprehensive Test (CT)
Admission runs by competition on CT results and on a fee-paying basis only.
Confirm your level of English
IELTS Academic from 5.0, TOEFL iBT from 65, TOEFL ITP from 460 — or a language interview with the admissions committee.
Submit your documents
Through admission.qairu.kz: ID card, bachelor’s diploma, 3×4 photo, medical documents, proof of payment.
Wait for the decision of the admissions committee
Once your application has been reviewed — enrollment.
Get a consultation
We will walk you through the program, the entrance tests and the payment — by phone or by email.
- 8 (700) 300 33 17
- info@nairu.edu.kz
Astana, 55/1 Mangilik El Ave., EXPO Business Center, block B 2.2
Mon–Fri, 09:00–18:00
QUESTIONS AND ANSWERS
Questions and answers
The professional master’s lasts one year and ends with a master’s project and industrial practice; the research and teaching one lasts two years, with a thesis, research work and preparation for teaching.
7M06102 · MASTER’S
One year to a new level in industrial AI
We will help you make sense of the requirements and the format — call or write to the admissions committee.
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