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This study analyzes the level of perceived and knowledgeable skills in Data Science applied to Cybersecurity among Computer Science students, in a context marked by the increase in digital threats and the growing demand for hybrid professional profiles. The objective was to evaluate these levels and explore their relationship with interest in specializing in these emerging areas. The methodology was based on a quantitative approach, with a non-experimental, cross-sectional, and correlational design. An online questionnaire was administered to Computer Science students, using Likert-type scales to measure perceived knowledge, skills, and self-efficacy in tasks related to data analysis and cybersecurity. The sample was non-probabilistic and selected for convenience, and the data were analyzed using descriptive and inferential techniques. The results show that the perception of knowledge and skills is moderate and heterogeneous. Less than 50% of students consider themselves competent in key tasks such as intrusion detection or security data analysis. Furthermore, little curricular integration between Data Science and Cybersecurity was identified, with limited practical opportunities. However, approximately half of the students expressed interest in specializing in these areas. It is concluded that a gap exists between the training received and the demands of the professional environment. Although students recognize the importance of integrating both disciplines and show a willingness to specialize, they perceive their preparation as insufficient. The need to redesign curricula is highlighted, incorporating integrated approaches and practical experiences that strengthen competencies and improve self-efficacy in this field.
Este obra está bajo una licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional.
