Navneet Sharma

I am Navneet Sharma, an aspiring data scientist with a strong foundation in Python, R, SQL, machine learning, and data analysis. With a keen interest in solving real-world problems using data-driven insights, I have actively participated in hackathons, internships, and research projects to refine my technical skills and problem-solving abilities. My experience spans across multiple domains, including healthcare automation, predictive analytics, and unemployment analysis.

I am proficient in data preprocessing, feature engineering, machine learning model development, and visualization tools such as Power BI and Excel. Additionally, I have a strong grasp of NoSQL databases (MongoDB) and SQL databases (MySQL, Oracle), enabling me to work efficiently with structured and unstructured data.

Hackathon Experience:

Smart India Hackathon 2024 (SIH 2024): Led a team as captain and advanced to Round 2 with a project focused on healthcare automation.

SEED Hackathon 2024: Participated and presented an AI-driven queue management system for healthcare, demonstrating innovative problem-solving and team collaboration.

Hack Sangraam (Medi-Caps University ACM Student Chapter): Participated in a DSA coding challenge on Hackerrank, showcasing algorithmic and coding skills.

Projects:

Vita Cure – AI-Driven Queue Management System

Developed an AI-based hospital queue management system that optimizes patient flow using real-time data and machine learning models.
The system enhances emergency response efficiency by prioritizing critical patients and reducing hospital wait times.
GitHub Repository: Vita Cure

Predictive Analytics for Car Pricing

Built a machine learning model to predict car prices based on various factors like kilometers driven, age, fuel type, and seller type.
Implemented regression and classification models to achieve high predictive accuracy.
GitHub Repository: Car Price Prediction

Unemployment Analysis in India

Conducted an in-depth analysis of unemployment trends in India using Python, Pandas, and Matplotlib.
Applied exploratory data analysis (EDA) and machine learning models to identify key factors affecting unemployment rates.

Technical Skills:

Programming Languages: Advanced Python, R, C/C++, Core Java

Databases: SQL (MySQL, Oracle), NoSQL (MongoDB)

Machine Learning: Supervised learning, feature engineering, model evaluation

Data Visualization: Power BI,MS Excel

Tools & Platforms: Scikit-learn, Pandas, NumPy, Jupyter Notebook

Certifications:

Data Visualization: Empowering Business with Effective Insights – Tata (Forage)

Databases for Developers: Foundations – Oracle Dev Gym

Certificate of Participation in SEED Hackathon

I am excited to bring my expertise and problem-solving mindset to this hackathon, collaborate with like-minded individuals, and create impactful solutions using data and AI.