Enhancing Employability Through an Advanced Mock Interview Platform for Fresh IT Graduates

In today's competitive job market, securing employment depends not only on possessing necessary qualifications but also on demonstrating an exceptional interview performance. Therefore effective preparation for interviews has become crucial for enhancing employability. Traditional mock interviews are often impaired by the lack of personalised feedback and real-time evaluation. This critical gap affects the candidates' ability to identify and address weaknesses, hindering efforts to refine their interviewing skills and maximise their chances of success. This research proposes the development of an advanced AI driven mock interview platform. This platform aims to bridge the existing gap in interview preparation methods by providing candidates with a personalised, interactive, and data-driven experience that empowers them to build confidence. The platform leverages Large Language Models (LLMs) to generate personalised interview questions tailored to a candidates experiences and qualifications. Then utilises Convolutional Neural Networks (CNNs) for multimodal analysis of non-verbal cues, offering insights to a candidate's confidence level. Additionally, it provides real-time feedback on communication skills, focusing on delivery, clarity, and tone. To further personalise the learning experience personalised recommendations will be facilitated. This multifaceted approach seeks to fundamentally redefine interview preparation and equip individuals with the necessary tools and confidence to thrive in the competitive job market.