Suleimenova L.
Candidate of Technical Sciences, Head of the Department of Computer Science, O.Zhanibekov South Kazakhstan Pedagogical University, https://orcid.org/0000-0002-4579-1622
Adylbekova E.
Candidate of Pedagogical Sciences, Acting Associate Professor, O.Zhanibekov South Kazakhstan Pedagogical University, https://orcid.org/0000-0003-1471-0137
Nakhimova V.
doctoral student, O.Zhanibekov South Kazakhstan Pedagogical University, https://orcid.org/0000-0002-4248-8943

Abstract
The use of machine learning methods makes it possible to more quickly introduce relevant tools and concepts into teaching practice. Machine learning (ML) offers individualized teaching methods that allow teachers to adapt programs for each student, taking into account their specific needs and level of training. The transition to online education and hybrid formats requires new learning strategies. Machine learning can help to adapt programs to these changes, making learning more flexible and efficient. Pedagogical programs based on machine learning methods provide future teachers with relevant skills and knowledge in the educational field.
In general, the application of machine learning methods in education, especially in the training of future computer science teachers, is today an urgent and promising topic that can bring significant innovations to educational practices and training of specialists.
The results of the study clearly demonstrate that the use of machine learning methods in the process of professional training of computer science teachers has a significant positive impact on their competencies and educational practice.

 Keywords: Machine learning, formation, competence, teaching methods, innovative methods.