GenZ Mentor 🧭

An AI-powered career exploration assistant built as a capstone project for the Google x Kaggle Generative AI Intensive Workshop (2025Q1).

🚀 Project Objective

GenAI Mentor aims to support students and professionals in reflecting on their career goals through conversational, personalized guidance. It uses generative AI to analyze survey responses and provide meaningful, context-aware feedback.

🧠 Key Features

• Embeddings & Semantic Search: Converts survey responses into vector embeddings to retrieve similar career paths or reflections.
• Retrieval-Augmented Generation (RAG): Integrates retrieved examples into prompts to generate contextually relevant responses.
• Structured Prompting with Few-Shot Examples: Ensures coherent, structured, and grounded output from the LLM.
• Interactive Loop: Supports multiple rounds of user interaction, with each new query generating fresh, relevant responses.

🔧 Tech Stack

• Gemini API (via Google AI Studio)
• Python
• Kaggle Notebooks
• LangChain / LangGraph (optional for agentic flow)
• FAISS / Vector Store (for embeddings search)
• Pandas / Numpy (data handling)

Dataset used: Understanding Career Aspirations of GenZ - Kaggle Dataset