Aspiring Associate Software Engineer
Motivated and detail-oriented Associate Software Engineer with hands-on experience in designing and developing responsive web applications. Skilled in HTML, CSS, JavaScript Basics, and Bootstrap for creating dynamic and user-friendly front-end interfaces. Experienced in Python, Java Basics, and SQLite for effective back-end development and database management. Proficient in using VS Code, Git, GitHub, and Streamlit for coding, version control, and deployment. Strong understanding of software development principles, debugging, and problem-solving, with a passion for writing clean, maintainable code and continuously learning new technologies to build efficient and reliable software solutions.
Hi, I’m Sivasankar Ajjada, a passionate B.Tech student in Computer Science and Engineering at Mohan Babu University, Tirupati, and an active learner at Nextwave CCBP 4.0 Academy. With a strong interest in software development, I am continuously improving my skills in both front-end and back-end technologies to build modern, scalable, and efficient applications.
I have hands-on experience with HTML5, CSS3, JavaScript Basics, Bootstrap, Python, Java Basics, and SQLite, and I enjoy working on projects that combine clean design with strong functionality. My focus is on writing maintainable code, solving problems effectively, and delivering reliable software solutions.
With curiosity, adaptability, and a drive for continuous learning, I aim to grow as a professional Associate Software Engineer and contribute to impactful projects in the tech world.
Developed a responsive and interactive food ordering web application inspired by Swiggy using HTML, CSS, and Bootstrap. The project features a clean, user-friendly interface with modular components, dynamic layouts, and seamless navigation, providing an engaging experience across devices. Optimized design ensures fast load times and consistent branding throughout the application.
Wine Quality Prediction is a machine learning web app that predicts wine quality based on chemical properties. After comparing multiple models, AdaBoost gave the best performance. The app is built with Python, Streamlit for the UI, and deployed for real-time predictions.
Professional certifications that validate my expertise and commitment to continuous learning
Let's discuss your next project or just say hello. I'm always open to new opportunities and interesting conversations.