AI-Powered Career Mentor

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  AI-Powered Personal Study Planner: Generates smart, personalized task roadmaps and reminders to optimize your learning workflow.

🌟 Inspiration

Choosing the right career path is one of the biggest challenges faced by students today. Many struggle with:

Lack of proper guidance.

Overwhelming number of online resources.

Uncertainty about whether to focus on jobs, higher studies, or entrepreneurship.

We wanted to create an AI-powered platform that acts like a personal mentor, helping students map their skills, choose a career path, and get recommendations on courses, projects, and placements. The inspiration came from the struggles we and our peers faced while preparing for IT/software and core company placements.

📘 What We Learned

While building this project, we gained experience in:

Designing recommendation systems using machine learning.

Integrating NLP-based chatbots to simulate mentorship conversations.

Understanding how to structure career roadmaps (skills → projects → jobs).

Working collaboratively with Git, APIs, and deployment tools.

We also learned to present solutions in a problem → approach → outcome format, which is essential for hackathons.

🛠️ How We Built It

Data Collection:

Gathered information on career paths, skills, and job roles.

Collected resources like online courses, certifications, and project ideas.

AI Engine:

Used a recommendation model to suggest career paths based on student interests and skills.

Implemented NLP for a chatbot-like experience to answer student queries.

Frontend & User Interface:

Built a simple dashboard where users can input their preferences.

Career roadmap is displayed visually for clarity.

Backend:

Python-based backend with APIs serving recommendations.

Database for storing user profiles and progress.

⚡ Challenges We Faced

Data Standardization: Organizing diverse data (courses, skills, jobs) into a consistent format.

Personalization: Ensuring recommendations are not too generic but tailored for each student.

Time Constraints: Implementing both AI and a working UI within hackathon deadlines.

Integration: Making sure the frontend, backend, and AI models communicated smoothly.

Despite the hurdles, we built a working prototype that provides students with a personalized AI mentor to shape their career journey.

Built With

• commandline
• csv
• excel
• github
• json
• kiro
• python
• steering
• vscode