A S Chethana User
@aschethanauser
Data science and ML graduate building real-world AI products with Python, TensorFlow, and production-ready APIs.
What I'm looking for
I’m a Computer Science and Business Systems graduate with hands-on experience in Data Science, Machine Learning, and AI. I enjoy turning messy data into models that perform in real-world settings, supported by strong Python-based engineering.
In my Data Science Internship at Prinston Smart Engineer, I built and deployed CarValue, a used-car price prediction application. I trained a Random Forest regression model on 8,128 historical listings (R² score of 0.86) and built a Flask REST API for real-time predictions with Firebase Google authentication and buyer/seller browsing modes.
I also ship practical AI experiences through projects like EduGPT with Your AI Instructor. Using Groq – LangChain – Gradio, I built an AI learning platform for automated syllabus generation, created a streaming mock interview engine with instant performance scoring, and deployed the full-stack Python app on Hugging Face Spaces for public testing.
Across work and projects, I focus on data preprocessing, model evaluation, and data visualization, and I collaborate across teams to deliver working systems—within a 4-month internship cycle. I’m quick to learn, enjoy teamwork, and aim to build reliable, production-ready ML/AI solutions.
Experience
Work history, roles, and key accomplishments
Data Science Intern
Prinston Smart Engineer
Feb 2026 - May 2026 (3 months)
Built a used-car price prediction application using a Random Forest regression model trained on 8,128 historical listings (R² = 0.86). Developed a Flask REST API for real-time predictions with Firebase Google authentication and implemented a 6-feature preprocessing pipeline with categorical encoding.
Education
Degrees, certifications, and relevant coursework
Canara Engineering College
Bachelor of Engineering, Computer Science and Business Systems
2022 - 2026
Grade: CGPA: 8.45 / 10
Pursuing a BE in Computer Science and Business Systems with a CGPA of 8.45/10.
Shri Ramakunjeshwara Pre University
Pre-University, Pre-University Program (PCMB)
2020 - 2022
Grade: Percentage: 76.83%
Completed Pre-University (PCMB) with a percentage of 76.83%.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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