Avantika Singh

About

Third-semester Computer Science Engineering student with a strong foundation in C, Python, and web technologies, plus hands-on exposure to machine learning through academic projects. Comfortable building and debugging small applications end-to-end, from data preprocessing to simple deployed prototypes.

Education

• B.Tech in Computer Science Engineering
  Symbiosis Institute of Technology, Nagpur
  Computer Science Engineering · 2025 – 2029

Skills

• C
• CSS
• Data Analysis
• HTML
• Data Interpretation
• Python
• Machine Learning
• JavaScript
• Model Evaluation
• Supervised Learning
• Unsupervised Learning
• Predictive Analytics
• Random Forest
• API Integration Understanding
• AI Model Evaluation
• Data Processing
• Machine learning model development
• Naive Bayes
• Support Vector Machine
• Algorithm implementation

Projects

• CampusFund — Industry-Driven Hackathon 2025

  Collaborated in a team of 4 at the Industry-Driven Hackathon 2025 (Symbiosis Institute of Technology, in association with GeeksforGeeks) to design CampusFund, a concept for student financial wellness through peer-to-peer lending. Helped prototype and present the solution under time constraints, dividing tasks according to individual strengths. Strengthened problem-solving, teamwork, and communication skills while working with peers from diverse academic backgrounds.

• Personal Portfolio Website
  HTML, CSS

  Designed and built a responsive personal portfolio website to showcase academic background, technical skills, and projects. Structured clean, semantic HTML and CSS layouts to ensure consistent display across screen sizes.

• Python Weather App
  Python, REST APIs

  Built a Python application that calls a public weather API to fetch real-time data for a user-specified location. Parsed and processed API responses to present temperature, humidity, and weather conditions in a readable format.

• Water Quality Monitoring using IoT & ML
  Python, SVM, Random Forest, Naive Bayes, Streamlit

  Built an ML-based system to assess water quality using sensor readings for pH, TDS, turbidity, and temperature. Preprocessed and cleaned raw sensor data, then trained and compared SVM, Random Forest, and Naive Bayes classifiers to predict water quality categories. Developed a Streamlit prototype to visualize sensor readings and model predictions for quick interpretation.

⚽ Extracurricular activities

• IEEE Student Branch — ExCom Member
• IEEE WIE Chapter — Vice Chair

🤝 Volunteering

• ICSIT 2026 — Symbiosis Institute of Technology, Nagpur · Technical Team Member · 2026