This interactive project utilizes natural language processing to create a Python Tutor Chatbot. It responds to user queries about Python concepts, provides code analysis, and offers explanations on common programming mistakes. The chatbot uses a knowledge base to determine the appropriate responses to user questions. The results are presented through an intuitive web interface, showcasing real-time interactions and code analysis feedback.

During the development of this Python Tutor Chatbot project, several challenges were encountered which required innovative solutions. One of the primary obstacles was creating a responsive and engaging chat interface, which was overcome by implementing a simulated typing effect using JavaScript. This allowed for a more natural conversation flow. Another significant challenge was presenting complex programming concepts in an easily understandable format for users who might not be familiar with Python. To address this, I implemented a structured knowledge base with clear explanations and examples, along with a code analysis feature. This approach made the learning experience more accessible and intuitive, enabling users to grasp Python concepts and identify common coding mistakes at a glance.