Task Submission: Project Topic Recommender

Student: Yella Navyasree (DAS003188)

Domain: AI & Data Science

Internship ID: 848

How I Built an AI Project Topic Recommender Using Python

As part of my AI & Data Science Internship, I completed a project called AI Project Topic Recommender. The objective of this project was to develop a Python application that recommends suitable project topics to students based on their skills, interests, and preferred domain.

Project Objective

The main goal of this project was to simplify the process of selecting project ideas. Instead of manually searching for suitable topics, the application analyzes a student's skills and recommends the most relevant projects using Natural Language Processing techniques.

Technologies Used

• Python
• Pandas
• NumPy
• Scikit-learn
• TF-IDF Vectorization
• Cosine Similarity
• Visual Studio Code
• GitHub

Features

• Student Profile Management
• AI-based Project Topic Recommendation
• Search Projects by Domain
• Search Projects by Difficulty
• Recommendation Report Generation
• Simple Command-Line Interface

How I Completed the Task

I first created datasets containing student information and project topics. After that, I implemented TF-IDF Vectorization and Cosine Similarity to compare student skills with project requirements. Based on the similarity scores, the application recommends the top matching project topics. I also added options to search projects by domain and difficulty level, making the application more useful and user-friendly.

Challenges Faced

Initially, I found it challenging to understand how recommendation systems compare text data. After learning TF-IDF and Cosine Similarity, I was able to implement an effective recommendation engine. I also improved my understanding of data handling using Pandas and organizing a Python project.

What I Learned

This project enhanced my knowledge of Python programming, data processing, Natural Language Processing concepts, recommendation systems, and machine learning fundamentals. It also improved my GitHub skills and project documentation practices.

Conclusion

Completing this project gave me practical experience in building an AI-based recommendation system. It increased my confidence in developing real-world Python applications, and I look forward to learning more advanced AI and Machine Learning techniques in future internship tasks.