Heart sound auscultation is a physical examination routinely used in clinical practice to identify potential cardiac abnormalities. However, accurate interpretation of heart sounds requires specialized training and experience, thereby limiting its generalizability. Deep learning, a subset of machine learning, involves training to learn from large datasets and perform complex tasks related to intricate patterns, such as disease diagnosis, event prediction, and clinical decision-making. Over the past decade, deep learning has been successfully applied to heart sound analysis with remarkable achievements. Meanwhile, as heart sound analysis is gaining attention, many public and private heart sound datasets have been established for model training. The massive accumulation of heart sound data improves the performance of deep learning-based heart sound models and extends their clinical application scenarios. STATEMENT: An exploratory study to find out the competency of assessing cardiac sounds in patients among nursing students in selected nursing colleges Kanpur, U.P. OBJECTIVES: 1. To find out the competency of assessing various cardiac sounds in patients among nursing students in selected nursing colleges Kanpur UP. 2. To find out the association between competency of assessing various cardiac sounds in patients among nursing students with their selected demographic variables. MATERIAL AND METHOD: The Quantitative Research Approach with Exploratory Research Design was adopted. The samples were selected by using non-probability convenience Random Sampling Technique. The Sample Size was 60 nursing students at selected nursing colleges of Kanpur, Uttar Pradesh. The data was collected by using OSCE Assessment on cardiac sounds. The collected data were analyzed by using Descriptive statistics and Inferential statistics. RESULT: The present study was aimed to find the competency of assessing cardiac sounds in patients among nursing students. The recent data was collected and analysed statistically based on objectives of the study. By performing OSCE examination on cardiac sounds we found that out of 60 nursing students, the majority of the nursing students 31(51.66%)have performed very well and have adequate level of competency, 24(40%) of the students have Moderate Competency and 5(8.34%) of the students have Inadequate Competency.