👋 Hey there! I'm Aditya Behera

🎯 AI/ML Enthusiast | Python Programmer | Lifelong Learner

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🧑‍💻 About Me

I'm a 3rd-year B.Tech. student majoring in Artificial Intelligence and Machine Learning at St. John College of Engineering & Management, University of Mumbai. Currently in Semester 5, I have a strong passion for data structures and algorithms, AI, and programming.

I enjoy building intelligent systems, solving real-world problems through code, and continuously exploring new tools and technologies in the AI/ML space. I'm focused on developing practical projects and open to opportunities that involve technology, innovation, and collaboration.

🔬 Technical Interests:

  • Artificial Intelligence, Machine Learning, Deep Learning
  • Computer Vision & Object Detection
  • Data Science & Smart Automation
  • Software Development and Deployment
8.71
CGPI
3+
Projects
5+
Certifications

💻 Core Skills

🤖

Artificial Intelligence (AI)

📜 AI & ML Technical Workshop (Remarkskill + IIT Bombay) 📜 Google AI Essentials 🔧 Tic-Tac-Toe with AI (Minimax Algorithm)
🧠

Machine Learning

📜 AI & ML Technical Workshop (Remarkskill + IIT Bombay) 💼 Advanced Computer Vision Internship (WISERLI) 📜 Google AI Essentials 🔧 Music Genre Classification (CNN)
👁️

Computer Vision

💼 Advanced Computer Vision Internship - YOLOvX (WISERLI) 🔧 YOLOvX Object Detection Project
🐍

Python Programming

🎓 St. John College of Engineering and Management 📜 The Complete Python Bootcamp From Zero to Hero 📜 AI & ML Technical Workshop (Remarkskill + IIT Bombay) 🔧 Multiple Python Projects (AI, ML, Computer Vision)
📊

Data Science

📜 Data Science Foundations (LinkedIn Learning) 🔧 Music Genre Classification (Data Analysis)

💼 Experience

👁️‍🗨️

Summer Intern – Advanced Computer Vision (YOLOvX)

WISERLI Pvt. Ltd.

📅 19 May 2025 - 28 May 2025 (10 days) 📍 Palghar, Maharashtra, India · Hybrid 🏢 Internship

Completed a 10-day summer internship with WISERLI Pvt. Ltd., focusing on real-time object detection using YOLOvX. Developed a smart tray detection system for identifying and counting canteen trays in dynamic environments.

🎯 Key Contributions:

  • Dataset Creation: Captured and annotated a custom dataset of 800+ images
  • Model Training: Trained and fine-tuned a YOLOv8n model achieving 85% mAP@0.5, 8 FPS
  • Deployment: Deployed the model on a YOLOvX mobile app for real-time testing
  • Documentation: Documented results and presented a demo on LinkedIn and YOLOvX community
  • Community Engagement: Shared detailed post on YOLOvX Community Forum with testing results and insights
YOLOv8 Computer Vision Object Detection Python Data Annotation Model Training Mobile Deployment
View Community Post View Certificate
☁️

Azure AI Virtual Internship (Microsoft-AICTE Initiative)

Edunet Foundation

📅 May 2025 - Jun 2025 (2 months) 📍 Remote 🏢 Internship

Successfully completed a 4-week virtual internship on AI & Azure, offered by Microsoft and implemented by Edunet Foundation in collaboration with AICTE.

💡 What I did:

  • Mentor-led Sessions: Attended sessions on AI, Machine Learning, Azure AI, and Generative AI
  • Hands-on Labs: Completed hands-on labs and self-paced learning through Microsoft Learn
  • Topics Explored: Supervised learning, computer vision, deep learning, and Copilot

🧠 Capstone Project:

  • Project: Developed a deep learning model to classify music into genres using the GTZAN dataset and spectrogram features
  • Implementation: Built and trained a CNN model for genre classification
  • Evaluation: Project evaluated by Edunet Foundation as part of the internship completion process
Azure AI Machine Learning Generative AI Python LibROSA TensorFlow Keras CNN
View GitHub Repo

🔧 Projects

🎮

Tic-Tac-Toe with AI

A Python-based multiplayer game where one player uses AI (Minimax) logic to make smart moves.

Python Minimax CLI
GitHub
🎵

Music Genre Classification

Internship Project

Capstone project for Azure AI Virtual Internship (Microsoft-AICTE Initiative). Developed a deep learning model to classify music genres using spectrograms of audio files from the GTZAN dataset.

  • 65% accuracy on test set with CNN architecture
  • Spectrogram feature extraction pipeline using LibROSA
  • Data preprocessing and augmentation techniques
  • Model evaluation and performance optimization
  • Project evaluated by Edunet Foundation for internship completion
Python CNN TensorFlow Keras LibROSA GTZAN Dataset
GitHub

📜 Certifications

👁️

Advanced Computer Vision Internship - YOLOvX

Wiserly

View Certificate
🧠

AI & ML Technical Workshop

Remarkskill + IIT Bombay

View Certificate
☁️

AI Azure Virtual Internship

Edunet Foundation

View Certificate
☕

Programming in Java

NPTEL

View Certificate
🐍

The Complete Python Bootcamp from Zero to Hero in Python

Udemy

View Certificate
🔍

Google AI Essentials

Google

View Certificate
📊

Data Science Foundations

LinkedIn Learning

View Certificate

🎓 Education

🎓

Bachelor of Technology (B.Tech.)

Artificial Intelligence and Machine Learning

St. John College of Engineering and Management

University of Mumbai

📆 2023 – 2027 📈 CGPI: 8.71 (Till Sem V)

📫 Connect with Me

📌 Always curious, always learning. Let's build something amazing!

LinkedIn GitHub