The article discusses the actual problems of practical training in the tourism and hospitality industries in Russia and identifies the main problems of training specialists at Russian specialized universities. The main focus is on building partnerships between universities and employer organizations in order to train highly qualified specialists. Purpose: The research is aimed at creating an effective model of practical training based on the interaction of the university with employer organizations within the framework of the training of specialists in the tourism and hospitality industries. Design/Methodology/Approach: The work is based on scientific publications devoted to evaluating the effectiveness of the existing system of personnel training for the tourism and hospitality industries, studying its features, building models of vocational education, and using practice-oriented programs in the training of specialists. To study the problems of practical training of personnel for tourism and hospitality, systematic and structural approaches were used as a methodological basis, as well as methods of analysis and synthesis, the study of models of cooperation between universities and employers, and methods of monitoring and evaluating the quality of training specialists. To obtain empirical data, an analysis of the needs of the labor market for specialists in the hospitality industry was carried out, as was the study of models of cooperation between universities and employers. Results: In the course of the work, the author has formed a model of practical training for specialists in the tourism and hospitality industries, including the purpose and objectives, process requirements, organization conditions, and requirements for the results of the process. The innovative nature of the proposals lies in the development of new models of practical training based on gamification technology. The direction of further research may include the development of a methodology for the organization of the university’s interaction with employer organizations in the framework of practical training. Conclusion: The results of the study can be used by professional educational organizations to organize the process of practical training of students, which will effectively solve the problem of training personnel for tourism and hospitality. The social consequences of organizing the process of practical training for students will include increasing the competitiveness of graduates in the labor market, improving the quality of tourist and hotel services, introducing innovations into the tourism and hospitality industries, and developing startups.

The reform of the training mode for English majors in the context of the new liberal arts is a dynamic process that conforms to social needs, continuously improves and optimizes. After a series of special investigations, this article proposes development ideas for the cultivation of English majors in local applied undergraduate universities based on the analysis of the demand for English majors' abilities in the job market. The aim is to solve the problems of unclear characteristics of English major talent cultivation in local applied undergraduate universities and weak competitiveness of graduates in employment.

Under the background of engineering education certification, the traditional personnel training model can’t meet the requirements of high-quality personnel training under the new engineering background. Taking Surveying and mapping engineering major of Liaoning Institute of Science and Technology as an example, this paper explores the continuous improvement of the output-oriented talent training model through collaborative education of talents training objectives, curriculum system, practical teaching system, teacher team construction, enterprises and graduates. Over the years, the surveying and mapping engineering major of our school has achieved good results in personnel training. The major actively ADAPTS to the regional development of the local economy, closely connects with the needs of regional talents, and highlights its characteristics in serving the local economy.

Credit risk assessment is one of the most important aspects of financial decision-making processes. This study presents a systematic review of the literature on the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques in credit risk assessment, offering insights into methodologies, outcomes, and prevalent analysis techniques. Covering studies from diverse regions and countries, the review focuses on AI/ML-based credit risk assessment from consumer and corporate perspectives. Employing the PRISMA framework, Antecedents, Decisions, and Outcomes (ADO) framework and stringent inclusion criteria, the review analyses geographic focus, methodologies, results, and analytical techniques. It examines a wide array of datasets and approaches, from traditional statistical methods to advanced AI/ML and deep learning techniques, emphasizing their impact on improving lending practices and ensuring fairness for borrowers. The discussion section critically evaluates the contributions and limitations of existing research papers, providing novel insights and comprehensive coverage. This review highlights the international scope of research in this field, with contributions from various countries providing diverse perspectives. This systematic review enhances understanding of the evolving landscape of credit risk assessment and offers valuable insights into the application, challenges, and opportunities of AI and ML in this critical financial domain. By comparing findings with existing survey papers, this review identifies novel insights and contributions, making it a valuable resource for researchers, practitioners, and policymakers in the financial industry.