ZenCode: A Unified AI-Driven Framework for Holistic Placement Preparation through Automated Skill Assessment and Interview Simulation

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Pramod Aswale
Vedant Manoj Chaudhary
Sameer Jitendra Patil
Tejas Jagganath Shinde
Siddharth Sagarkumar Roy

Abstract

The transition from academic environments to professional career landscapes presents significant hurdles for students, requiring a multi-faceted approach to skill development. While independent tools for coding or resume building exist, there is a lack of integrated platforms offering a cohesive preparation journey. This paper introduces ZenCode, a one-stop placement preparation solution featuring four integrated modules: Aptitude, Company-wise Data Structures and Algorithms (DSA), AI-Assisted Resume Building, and AI Mock Interviewing. We detail the system architecture, which follows a modern MERN (MongoDB, Express, React, Node.js) stack , and the integration of Generative AI services for personalized feedback. We evaluate the system’s effectiveness in enhancing student readiness for technical and soft-skill evaluations.

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How to Cite
Aswale, P., Chaudhary, V. M., Patil , S. J., Shinde, T. J., & Roy, S. S. (2026). ZenCode: A Unified AI-Driven Framework for Holistic Placement Preparation through Automated Skill Assessment and Interview Simulation. International Journal on Advanced Computer Engineering and Communication Technology, 15(1), 49–55. Retrieved from https://journals.mriindia.com/index.php/ijacect/article/view/1867
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