IETU, daprtment PE, 2025 - present time
2018 - 2022 AUPET named after G.Daukeev. Automatization and control.
2022 - 2024 Al Farabi KazNU. Business Intelligence and Big Data.
Artificial intelligence, machine learning, Bayesian networks
Wójcik, W., Shayakhmetova, A., Akhmetova, A., Abdildayeva, A., & Nurtugan, G. (2024). OPTIMIZING TIME SERIES FORECASTING: LEVERAGING MACHINE LEARNING MODELS FOR ENHANCED PREDICTIVE ACCURACY. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 14(4), 115–120. https://doi.org/10.35784/iapgos.6295
Abdildayeva A., Shayakhmetova A., Nurtugan G. B. Integrated Bayesian Networks and Linear Programming for Decision Optimization //Mathematics. – 2025. – Т. 13. – №. 23. – С. 3749.
ABDILDAYEVA A. et al. STOCK CLOSING PRICE FORECASTING USING LSTM, SENTIMENT ANALYSIS, KALMAN FILTER //JOURNAL OF COMPUTER SCIENCE. – 2024. – Т. 20. – №. 11. – С. 1388-1396.
The purpose of this discipline is to teach students the basic concepts, methods and technologies of artificial intelligence, as well as to develop their practical skills in developing AI applications and integrating them into IT projects. After completing the course, the student will have an understanding of the basic approaches to the creation and use of artificial intelligence, will be able to develop and implement AI solutions in various areas of IT, as well as analyze and optimize their performance and efficiency.