UDHAYA SWATHIKA

Detail-oriented and results-driven Data Analyst with academic and internship experience in data science, MIS reporting, and business analytics. Skilled in Python, SQL, Excel, Power BI and machine learning, with a passion for turning raw data into actionable insights. Completed a Master's in Data Science with a strong CGPA 9.12. Adept at creating reports, handling CRM systems, and supporting data-driven decision-making. Fast learner with strong communication and collaboration skills, seeking opportunities in data-centric roles across dynamic industries. Immediately available in Dubai on Visit Visa.

Project Name: Density-based Traffic Prediction

Domain: Traffic Management

Tools: Python, Deep Learning (CNN), Historical data analysis

Project Overview:

• Density-based traffic prediction using deep learning to forecast traffic conditions by analyzing vehicle density, counts, speeds, and environmental factors.

• Utilizes historical data to predict future traffic flow and identify patterns and congestion trends. • Enables real-time adjustments to traffic signals and planning for smarter, more efficient transportation networks.

• Aims to improve road network efficiency, reduce delays, and enhance overall traffic safety.

Project Name: Face Emotional Detection

Domain: Computer Vision / Emotion Recognition

Tools: Python, Machine Learning, Computer Vision

Project Overview:

• Develops a system to recognize and interpret human emotions from facial expressions using ML models.

• Explores CNN and SVM approaches for robust emotion detection in real-time or near-real-time scenarios.

• Addresses challenges in facial emotion recognition and aims to provide objective analysis of emotions.

Project Name: Twitter Sentimental Analysis

Domain: Natural Language Processing / Social Media Analytics

Tools: NLP, Python, Machine Learning

Project Overview:

• Builds a sentiment analysis model to detect sentiments from tweets.

• Applies NLP techniques and ML algorithms to gauge public opinion and track sentiment changes over time.

• Supports applications in monitoring brand perception, customer satisfaction, and public response to topics.