I’m Avnish Agrawal, a B.Tech CSE (AI/ML) student at VIT Bhopal University. I have hands-on experience in Python development, AI model building, and web applications through internships at JEE Simplified, UptoSkills, and Edunet Foundation (Microsoft Program). I’m passionate about building AI-driven solutions and solving real-world problems through code.
| Languages | |
|---|---|
| Python | |
| Java | |
| SQL | |
| C++ |
| Frameworks & Libraries | |
|---|---|
| python-telegram-bot | |
| TensorFlow | |
| Keras | |
| OpenCV | |
| Streamlit | |
| Tkinter | |
| BeautifulSoup |
| Tools & Platforms | |
|---|---|
| Git | |
| GitHub | |
| Visual Studio Code | |
| Wix Studio | |
| Velo (Wix) | |
| Microsoft Azure |
| AI & Platforms | |
|---|---|
| n8n | |
| Cursor | |
| Kiro | |
| Gemini CLI | |
| Claude Code | |
| Google AI Studio | |
| Google Antigravity | |
| AI Agents | |
| Google FireBase Studio |
- Python Development Intern @ JEE Simplified (Nov 2025 – Feb 2026)
- Developed Python-based Telegram bots to automate quizzes, student segmentation, and batch-wise group management.
- Web Development Intern @ UptoSkills (Oct 2025 – Jan 2026)
- Contributed to an AI-based resume builder, improving generation workflows and resolving formatting/output inconsistencies.
- AI & Azure Intern @ Edunet Foundation (May 2025 – June 2025)
- Explored Cloud, ML, and Generative AI through the Microsoft AI & Azure Internship Program.
A modern, full-stack expense sharing application built with Next.js, TypeScript, and Supabase. Perfect for splitting bills with friends, roommates, or travel companions.
Stock Trend Prediction App is a Streamlit-powered web interface that utilizes a pre-trained LSTM model to forecast stock closing prices. It provides interactive data visualizations, moving average analysis, and future trend predictions.
A machine learning-powered web app to predict diseases from symptoms. Built with Python and Streamlit to empower users with personalized health insights.
A Flask web app that detects crop diseases from leaf images using a CNN (VGG16). Built with Keras, OpenCV & Flask for real-time predictions.
- 17th Position in Coderaid (Oblivion’25, NSUT) – A national-level coding hackathon on Unstop.
- Finalist, Industry Conclave 2024 – Advanced to final round among top campus teams after multi-stage innovation pitching.
- Hackathon Participant, Odoo Hackathon 2025 – Competed in a national-level product-building sprint.