Sreedhar Rongala

I am a master’s student in Data Science at the University of Naples Federico II, specializing in Intelligent Systems. My academic journey is complemented by three years of hands-on experience in Data Analysis. My work focuses on extracting insights from complex datasets, leveraging machine learning, and developing data-driven solutions to real-world problems.

Through my studies and professional experience, I aim to deepen my expertise in machine learning and big data applications to drive impactful decisions in various industries.

I have three years of professional experience in data analysis, during which I worked on extracting actionable insights from data and solving complex business problems. My career highlights include:

Machine Learning & Predictive Modeling:

• Developed and optimized predictive models to improve production efficiency, reduce costs, and enhance customer satisfaction.
• Worked on churn prediction, boosting annual revenue by implementing data-driven strategies.

Industry Experience:

• At cedlearn and cl soft, I utilized advanced analytics tools to create visualizations and deliver insights.
• As part of a Smart India Hackathon team, I developed an object detection system.

Internship & Academic Work:

• Built predictive models and created dashboards during internships.
• Published work on deploying Flask applications and other practical data science solutions.

This hands-on experience complements my current pursuit of a master’s degree in Data Science, enhancing my ability to merge theoretical knowledge with practical applications.

Master’s Program in Data Science:

• Specialized coursework in Machine Learning, Big Data Analytics, and Intelligent Systems at the University of Naples Federico II.
• Hands-on projects integrating theoretical concepts with practical applications.

Industry-Specific Training:

• Practical experience in predictive modeling and data visualization during internships and professional roles.
• Advanced training in Python, R, and SQL for data manipulation and analysis.

Hackathon Experience:

• Participated in the Smart India Hackathon, where I contributed to developing an object detection system.

Continuous Learning:

• Self-directed learning in frameworks like Flask and FastAPI to enhance deployment skills.
• Exploration of YOLO models for object detection tasks.

This diverse blend of academic and hands-on training enables me to approach data challenges with both depth and practicality.