Name: Supratik Mitra
Email ID: supratik.g37python@gmail.com
College Name: Dr. Sudhir Chandra Sur Institute of Technology & Sports Complex
Branch/Specialization : B.Tech in Computer Science and Engineering (AI & ML)
College ID: 25500123169
Course Opted: 6-Month Project-Based Internship in Artificial Intelligence & Machine Learning
Instructor Name: Gaurav Sir
Duration: 6 Months
Trainer Name: Gaurav Patel
Trainer Email ID:gaurav.patel.gpp@gmail.com
Trainer Designation:Data Science Instructor
- Overall Learning
- Projects Completed
- Project 1: IntelliLearn-AI
- Project Introduction
- Technologies Used
- Roles and Responsibilities
- Project Report
- References
- Learnings from LST & SST
- Community Services
- Certificate
- Acknowledgments
During this internship, I gained practical knowledge in Artificial Intelligence and Machine Learning through hands-on project development and real-world problem solving. I learned important concepts related to data analysis, machine learning models, Retrieval-Augmented Generation (RAG), Natural Language Processing, and AI-based educational systems.
I developed skills in Python programming, data preprocessing, model training, vector databases, semantic search, and Streamlit application development. I also gained experience in integrating Large Language Models (LLMs), building intelligent workflows, and developing interactive AI applications.
Through the development of the IntelliLearn-AI project, I improved my understanding of project architecture, debugging, documentation, database integration, and deployment-oriented development. This internship also helped me strengthen my problem-solving abilities, analytical thinking, teamwork, and professional project handling skills.
Project 1: IntelliLearn-AI — Modular AI Study Assistant with RAG, ML and Evaluation System
IntelliLearn-AI is an AI-powered educational platform developed to enhance interactive and intelligent learning using Retrieval-Augmented Generation (RAG), Machine Learning, and Large Language Models (LLMs). The system allows users to upload study materials in PDF format and interact with them through AI-assisted features such as question answering, summarization, note generation, MCQ evaluation, subjective answer evaluation, and student performance prediction.
The project integrates semantic search using FAISS vector databases, HuggingFace embeddings, Groq LLaMA models, and machine learning algorithms to create a modular educational ecosystem. It also includes analytics dashboards, conversational memory, MongoDB-based learning history, and downloadable educational reports for improved learning support and evaluation.
Through this project, I gained practical experience in AI system development, machine learning workflows, NLP applications, data analysis, database integration, and deployment using Streamlit.
IntelliLearn-AI is designed to provide an intelligent and interactive educational learning platform using Artificial Intelligence and Machine Learning technologies. The system transforms traditional static study materials into an AI-assisted learning ecosystem capable of answering questions, generating notes, evaluating student responses, and supporting personalized learning workflows.
The project focuses on combining Retrieval-Augmented Generation (RAG), semantic search, Large Language Models, and machine learning techniques into a unified educational platform. It aims to improve accessibility, learning efficiency, and automated educational assistance for students through intelligent document interaction and analytics-driven support.
- Programming Language: Python
- Frontend Framework: Streamlit
- LLM API: Groq
- LLM Model: LLaMA 3.1
- Vector Database: FAISS
- Embeddings: Sentence Transformers
- Machine Learning Framework: Scikit-learn
- Database: MongoDB
- PDF Processing: PyPDF2
- Data Analysis: Pandas and NumPy
- Visualization: Matplotlib
- Designed and developed the IntelliLearn-AI application architecture.
- Implemented Retrieval-Augmented Generation (RAG) based PDF interaction system.
- Integrated Large Language Models for educational assistance and evaluation.
- Developed Machine Learning modules for student performance prediction.
- Performed dataset analysis, preprocessing, and visualization.
- Integrated MongoDB for storing educational analytics and learning history.
- Developed MCQ evaluation and subjective answer assessment modules.
- Handled testing, debugging, documentation, and deployment-related tasks.
- Streamlit Documentation
- LangChain Documentation
- FAISS Documentation
- Scikit-learn Documentation
- Groq API Documentation
- MongoDB Documentation
LST and SST sessions played an important role in improving both my technical understanding and professional development throughout the internship period. These sessions provided valuable exposure to industry-oriented practices, communication techniques, and structured learning methodologies which helped me become more confident and disciplined in my approach towards project development and teamwork.
Through these sessions, I improved my communication skills, presentation abilities, and interpersonal interaction skills. Participating in discussions, collaborative activities, and learning exercises helped me develop confidence while expressing ideas, explaining technical concepts, and working effectively in team-oriented environments.
The sessions also helped me understand the importance of problem-solving, analytical thinking, time management, and proper documentation practices in real-world project development. I learned how structured planning, consistency, and systematic execution contribute significantly towards successful completion of technical projects and assignments.
In addition, LST and SST sessions provided guidance regarding professional ethics, workplace expectations, collaborative learning, and continuous self-improvement. These learnings helped me maintain a more organized and professional workflow during the development of the IntelliLearn-AI project and strengthened my understanding of practical implementation strategies.
Overall, the LST and SST sessions contributed significantly to my personal growth, professional readiness, and understanding of real-world project environments. The experience gained from these sessions enhanced both my technical confidence and my ability to work responsibly and effectively in academic as well as professional settings.
During my internship period, I actively participated in community-oriented activities focused on social responsibility and public welfare. These activities helped me understand the importance of contributing positively to society and working collaboratively for community development.
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Tree Plantation Drive – Participated in tree plantation activities near Dunlop, Kolkata and contributed towards promoting environmental awareness and greener surroundings.
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Food Distribution Activity – Participated in food distribution activities near Dunlop, Kolkata as part of social service and community support initiatives for needy people.
- Contributed towards environmental improvement through plantation activities.
- Supported community welfare initiatives by helping in food distribution activities.
- Improved communication, coordination, teamwork, and social responsibility skills.
- Gained practical exposure to community service and collaborative volunteering activities.
The internship certificate serves as an official acknowledgment of the successful completion of my training period. It will be issued by the organization upon fulfilling all required tasks and meeting the performance expectations of the program. The certificate validates the skills, experience, and contributions made during the internship.
- Prof. Radhakumari Challa , Executive Director and Founder - SURE Trust