Nandan Kumar Nalla

Hyderabad

Summary

Dynamic and results-driven intern at Ebox, proficient in Java and SQL database management. Demonstrated strong problem-solving skills while optimizing CRUD operations and enhancing data integrity. Adept in object-oriented programming and web fundamentals, with a solid foundation in Docker and Kubernetes, ready to contribute effectively to innovative projects.

Overview

Certification

Work History

Internship

Ebox,

05.2024 - 07.2024

Gained hands-on experience in Java programming, focusing on core object-oriented concepts such as classes, inheritance, exception handling, and collections.
Learned how backend systems work, including JDBC (Java Database Connectivity), and implemented CRUD (Create, Read, Update, Delete) operations to understand data flow between applications and databases.
Wrote and optimized SQL queries to retrieve, update, and manage data efficiently, ensuring data consistency, integrity, and performance optimization.
Hyderabad, India, vanasthalipuram, Hyderabad, telangana, 500070

Education

B.E/B.Tech - Information Technology

CVR COLLEGE OF ENGINEERING

Hyderabad

06-2025

Skills

Programming concepts: Java, Python, and basic JavaScript
Object-oriented programming
Problem solving
SQL database management

Web fundamentals: HTML and CSS
Basic DevOps: Docker and Kubernetes
Data structures: arrays, strings, linked lists, stacks, queues, trees, graphs

Websites

Languages

English
Telugu

Projects

➤JAVA ATM MACHINE

Source-code: https://github.com/rajyash1904/ATM-Machine.git,

Description:

Developed a console-based ATM simulation in

Java, incorporating secure user authentication via account number and password verification. Implemented key banking functionalities such as deposits, withdrawals, and balance inquiries using object-oriented programming and robust exception handling for an enhanced user experience.,

➤ Credit Card Fraud Detection Using Fuzzy Logic And Neural Network

Source-code: https://github.com/nandul297/CreditCard-FraudDetection-Using-Fuzzylogic,

Description:

Developed a sophisticated Credit Card Fraud Detection system using Python, leveraging Long Short-Term Memory (LSTM) networks for pattern analysis. Implemented fuzzy logic for realtime risk classification and utilized CSV data for extensive model training and evaluation.