AUTOMATED COLLEGE ASSISTANT CHATBOT USING PYTHON
Abstract
Abstract
This study presents the design and implementation of an Automated College Assistance Chatbot developed using Python. The system is intended to provide students with immediate responses to common academic and administrative inquiries, including admission requirements, course registration procedures, departmental regulations, and campus services. The chatbot employs Natural Language Processing (NLP) techniques to enable context-aware, human-like interactions, thereby enhancing the quality of information delivery. The methodology integrates Python-based frameworks, text-processing algorithms, and a conversational interface to ensure usability and reliability. System evaluation demonstrates that the chatbot significantly reduces response time, improves accessibility to institutional information, and offers a scalable and cost-effective tool for supporting student engagement. This project underscores the potential of AI-driven conversational agents to enhance communication processes within academic environments and contribute to improved institutional efficiency.
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