Regular consultations between the department leadership and our student body and alumni are ongoing. On December 23, a feedback session was held with alumni of the undergraduate Professional Educational Programme in "Data Science and Mathematical Modelling" ("Machine Learning and Mathematical Modelling" since 2025). The meeting featured active contributions from the Programme Guarantor, Associate Professor Violeta Tretynyk; Head of the Department Danylo Tavrov; and Department Professors Oleg Chertov and Igor Orynyak. The alumni cohort was represented by 2025 graduates Boryslav Krakovych, Maksym Shkarupylo, and Uliana Husar; 2024 graduates Maksym Sokolnytskyi, Bohdana Zlotenko, and Bohdan Pylypchenko; and 2023 graduates Mariia Pinda and Kirill Danylenko.

While the alumni expressed overwhelmingly positive reflections on their educational experience within the department, they brought forward strategic insights regarding the structural evolution of the degree programme and specific pedagogical enhancements for core modules. The following recommendations were submitted by the alumni panel:

• Expand the scope of the Optimisation Methods and Operations Research course component to incorporate a wider array of contemporary optimization algorithms.

• Introduce new elective course components dedicated to the mathematical modelling of UAV flight dynamics and control systems.

• Evaluate the introduction of a specialised elective module on digital signal processing (DSP), with a distinct focus on AI-driven audio wave analysis.

• Integrate the FAIR Data Principles (Findability, Accessibility, Interoperability, and Reusability) directly into the syllabi of all data-centric course components.

• Explore introducing a specialized elective course component dedicated to Category Theory as an advanced extension of functional programming.