The Effectiveness of Flipped Classroom to Develop Data Scientist Skills for Final year Project: A Case Study of Customer Facial Recognition Using CNN

The objective of this project is to introduce the effectiveness of flipped classroom to improve computing skills through a case study of a facial recognition system that can identify regular customers and improve customer service at Café, UTP. The flipped classroom has been implemented in Artificial Intelligence (AI) course to help students to improve computing skills focusing on AI domain. This method has also been applied to other AI related courses such as Machine Learning (ML) and Data Science (DS) to leverage the fundamentals of AI and its applications. This method was conducted on lab sessions and Final Year Project (FYP). About 7 to 8 lab sessions have been conducted and FYP on predictive analytics has been implemented using this method. The current challenges in identifying regular customers and understanding their behavior using membership cards are inconvenience and security risks due to the possibility of losing, expiring or becoming outdated. The project aims to overcome these issues by proposing a facial recognition technology using a convolutional neural network (CNN) algorithm. The model will be trained to classify and identify customers based on their facial features and labeled images of their faces will be stored in a database to verify their status as regular customers. The goal of this project is to create a dependable system that can accurately identify the regular customers of Café, UTP. The findings of this study suggest that the flipped classroom method can be an effective way to develop computing skills.