SmartPath📚🎓

Our project for the Aeravat 1.0 national level AI Hackathon conducted at Sardar Patel Institute of Technology.

Working of the Project

SmartPath.reduced.mp4

Personalized Career Roadmap for Engineering Students🚀

Problem Statement

As a second-year engineering student, it can be challenging to navigate the path towards your dream role or job after graduation. This application aims to provide personalized guidance to help students achieve their career aspirations by dynamically adjusting the timeline based on their current academic year and desired career path.

Key Components

1. User Input and Dream Role Specification

• Prompt the user to input their current year of engineering and specify their desired career path, industry preferences, technology interests, and career aspirations.

2. Skill Assessment and Gap Analysis

• Analyze the user's academic background, coursework, projects, and extracurricular activities to assess their current skill set and proficiency level.
• Identify skill gaps and areas for improvement by comparing the user's skills to the requirements of their dream role.

3. Dynamic Timeline Generation

• Develop algorithms to dynamically generate a timeline for skill acquisition and career preparation based on the user's current academic year and timing of campus placements.
• Adjust the timeline iteratively as the user progresses through their academic journey and updates their career goals.

4. Technology Stack and Learning Resources

• Recommend specific technologies, programming languages, frameworks, tools, and platforms relevant to the user's dream role and industry preferences.
• Provide curated lists of online courses, tutorials, books, and other learning resources to help the user acquire necessary skills and knowledge.

Technology Stack

• Frontend: TypeScript, Next.js, Tailwind CSS
• Backend: Python, Flask, Node.js, MongoDB
• AI: LangChain for natural language processing and Web scraping for data gathering.

Challenges

1. Timely Preparation: Ensure the user is adequately prepared with the required skills before the commencement of campus placements.
2. Skill Relevance: Recommend skills and technologies aligned with the user's desired career path and industry trends.
3. Dynamic Adjustments: Adapt the timeline and recommendations based on the user's changing academic year and evolving career goals.

Guidelines

• Dynamic Timeline Generation: Develop algorithms to adjust the timeline based on the user's academic year and placement season timing.
• Personalized Recommendations: Recommend tailored skills to learn, projects to undertake, and resources to explore based on the user's profile and career objectives.

Conclusion

By addressing these challenges and implementing the proposed solution, the application aims to empower engineering students with personalized career guidance, ensuring they are well-prepared for success in their future careers.