Learning outcomes and competencies

LО1. Know and understand the main patterns of the history of Kazakhstan, the fundamentals of philosophical, socio-political, economic, natural science and legal knowledge, and communicate orally and in writing in Kazakh, Russian and foreign languages.

LО2. Apply methods of scientific research, artificial intelligence and academic writing in the field of study; observe the principles of academic integrity; implement inclusive principles in professional activities; and demonstrate knowledge of the practical foundations of physical education.

LО3. Organize production processes and human resource management in agricultural enterprises based on a critical assessment of the forms and methods of the modern economy and regulatory legal documents. Determine the need for material, technical, financial and human resources; ensure occupational safety; and plan and manage projects to achieve professional objectives.

LО4. Demonstrate skills in working with information in global computer networks to conduct research and innovation activities in agronomy; classify the main areas of biological science; and develop competencies in searching for, analysing and applying digital resources to solve professional tasks.

LО5. Study the morphological and biological characteristics of the growth and development of agricultural plants, as well as the physiological processes of biomass accumulation, combined with the analysis of biochemical indicators, to assess crops and predict yields in precision agriculture systems. Master methods for assessing the genetic potential of varieties and applying digital breeding modelling to adapt plants to climate change.

LО6. Develop competencies in identifying soil types and varieties, mastering methods for restoring soil fertility, designing soil and agrochemical maps, and calculating fertilizer application rates. Use GIS technologies and remote sensing data to map soils and assess their parameters, analyse agrochemical indicators and optimize fertilizer application.

LО7. Develop competencies in classifying diseases and pests of agricultural crops, identifying harmful insects and phytopathogens, and applying methods for detecting diseases and predicting their spread using digital models. Master the development of integrated plant protection systems using biological, chemical and digital methods (GIS, drones and artificial intelligence); acquire skills in the storage and examination of crop products; and study quality standards and certification procedures.

LО8. Develop competencies in applying digital technologies and programming to solve agronomic tasks. Master the use of machine learning models for yield prediction, information system design, and Python programming for data analysis and process automation, including climate modelling, IoT and GIS. Integrate IoT and AI solutions, process spectral data (NDVI), use multispectral imagery to monitor crops and predict plant stress conditions.

LО9. Develop practical skills in applying modern digital technologies in agronomy; master the configuration and monitoring of hardware and software used at agricultural enterprises; conduct comprehensive monitoring of cropland conditions; configure UAVs for aerial photography; program autopilots and robots to perform agricultural operations; and interpret drone data to create digital field maps. Integrate data into cloud systems and select machinery operating modes based on GPS and sensor data in precision agriculture systems.

LО10. Analyse the economic efficiency of digital projects (KPI, ROI); manage digitalization projects in the agro-industrial complex; develop business plans for implementing IoT and AI; organize the work of personnel and make managerial decisions; calculate resource requirements and prepare process maps; assess risks; and take measures to ensure safety and occupational health and prevent injuries during the operation of automated machinery.