🎓 B.Tech in CSE (AI & ML) @ Sasi Institute of Technology and Engineering (CGPA: 8.32, graduating 2026). 🤖 AI & ML enthusiast with hands-on experience in Python, TensorFlow, Scikit-learn, and OpenCV. 💻 Skilled in data preprocessing, supervised & unsupervised learning, model evaluation, and integrating AI into full-stack apps. 🌐 Experienced in Full-Stack Development using React.js, Node.js, Express.js, MongoDB, SQL. 🛠️ Strong problem-solving, model building, and scalable web app development skills 🎯 Completed multiple internships (Full-Stack & ML). 💼 Looking for internship roles that allow me to learn, grow, and add value to the team. 📫 Reach me anytime at: chintharavikumar9908@gmail.com

• OOPs, DSA, SDLC, REST APIs, MVC Architecture
• Supervised & Unsupervised Learning, Data Preprocessing, Model Evaluation Metrics
• Communication, Public Speaking, Analytical Thinking, Problem-Solving, Leadership, Learning Agility, Time Management

• QuickCalc: Simple and user-friendly web-based calculator built with HTML, CSS, JavaScript (GitHub) (Demo).
• QuizzyBee: Fun and interactive quiz application built with React, Vite, featuring multiple-choice questions, score tracking, and animated background effects (GitHub) (Demo).
• Tic Tac Toe: Classic Tic Tac Toe game with real-time score tracking, built using HTML, CSS, JavaScript (GitHub Link) (Demo Link).
• Snake Game: A fun and classic Snake Game built with Python, Pygame (GitHub) (Demo).
• DocSpot: Full-stack healthcare appointment system with role-based access (Customer, Doctor, Admin) using Node.js, Express.js, MongoDB (GitHub) (Demo).
• Bubble Shooter Game: Interactive Bubble Shooter arcade game built with HTML, CSS, JavaScript (GitHub) (Demo).

• Car Price Prediction: Predict car market value using Machine Learning with features like brand, model, year, mileage, and fuel type (GitHub) (Demo).
• SONAR Rock vs Mine Prediction: Machine learning project to classify sonar signals as Rock or Mine using Logistic Regression (GitHub) (Demo).
• Customer Churn Prediction: Machine learning project to predict customer churn using Random Forest, XGBoost with data preprocessing, visualization, and SMOTE for class balancing (GitHub) (Demo).

Full Stack Development Intern – SmartInternz (May–July 2025)

• Built & deployed DocSpot, optimized React & MongoDB for 30% performance improvement.
• Integrated role-based authentication and enhanced UI/UX for seamless appointment booking.

Machine Learning Intern – SkillDzire (May–July 2024)

• Developed ML models with 85% accuracy on real-world datasets.
• Applied data preprocessing, feature scaling, and visualization using Pandas & Matplotlib.

AI/ML Virtual Intern – AICTE Eduskills (Jan–Mar 2024)

• Trained SVM, KNN, Decision Tree models achieving 80–90% accuracy.
• Built pipelines for classification tasks and evaluated models with Precision, Recall, F1 Score.

GSTN Hackathon 2024 – ML Developer

• Achieved 97.58% accuracy on a predictive model using Random Forest for GST data.
• Led a team of 4 developers, performing end-to-end EDA, feature engineering, model comparison, and documentation.

• AI Skills Passport (2025) – EY & Microsoft
• Generative AI Studio (2025) – Google Cloud (Simplilearn)
• Android Developer Virtual Internship (2024) – Google, AICTE & EduSkills
• Machine Learning Internship (2024) – SkillDzire
• Master Data Science in Python (2024) – Great Learning
• AI/ML Virtual Internship (2023) – Google, AICTE & EduSkills
• OpenCV Bootcamp (2023) – OpenCV University
• Web Development Internship (2023) – CodeWays
• Introduction to Cybersecurity (2023) – Cisco Networking Academy

NSS Volunteer – SASI Institute of Technology & Engineering (2022–2025)

• Organized blood donation camps and cleanliness drives impacting 500+ people.
• Coordinated 50+ volunteers, developing leadership and teamwork skills.