Despite years of anticipation regarding the transformative impact of Machine Learning and Artificial Intelligence in the field of education, the current landscape reveals a persistent reliance on conventional learning models, with a substantial portion of computer-based learning adhering to long-established educational practices (Krstić et al. in Artificial Intelligence in Education: A Review. 223–228 (2022)). The objective of this paper is to address the limitations of traditional approaches and online educational applications, by creating an application designed around personalized learning and user interaction. In order to achieve this, technologies such as Reinforcement Learning (RL) and Natural Language Processing (NLP) were used to enable personalization of the educational content around the user, as well as improve engagement of the user towards learning. The entire training process is conducted by an interactive chatbot that interacts with users in educational quizzes aligned with their personalized learning paths, thus ensuring that the users stay engaged. Initial feedback from a survey involving students using the application underscores a substantial improvement in the quality of learning when compared to conventional educational platforms. This improvement is attributed to factors like increased interactivity and personalization, emphasizing the application’s effectiveness in fostering enhanced academic outcomes for learners. While the current scope of the application primarily focuses on enhancing the learning experience for students preparing for campus placement interviews, the implications of this study extend beyond this, as the methodologies employed can serve as a blueprint for improving traditional educational applications. By integrating transformative technologies like Natural Language Processing and Reinforcement Learning, this paper aims to outline the potential in fostering increased interactivity and personalization to enhance academic outcomes across various educational contexts.