Venkata Satya Sai Pavan Kotti

Experienced in software testing, artificial intelligence, and full stack web development with a strong foundation in Python, Java, and C programming. Demonstrated expertise in maintaining up-to-date knowledge of industry trends and advancements, conducting software testing and validation procedures, and developing AI-driven applications. Proficient in front-end frameworks like HTML, CSS, and JavaScript as well as back-end technologies including Node.js and Express. Adept at utilising version control systems like Git for efficient collaboration. Career goal: to leverage technical skills to contribute to innovative software solutions.

Internet Surfing

Travelling

Learning languages

Content creation

Team work

Podcasting

MY HOME DEL

Frontend and Backend developer

Overview of the Project:

• Back-End: Python (using Flask or Django).
• Front-End: HTML, CSS, JavaScript ( use Bootstrap or Materialize for faster styling).
• Database: SQLite or PostgreSQL to store user information, products, orders, and delivery statuses

ONLINE BOOK STORE

Admin

Overview : The system allows users to browse, search, and purchase books. It will have multiple roles, such as an Admin and a User. The Admin can manage books (add, update, delete), while Users can browse books, add them to their cart, and proceed with a checkout.

Full-Stack Development:

• Front-end: HTML, CSS, JavaScript (React or Angular, or Vanilla JS ).
• Back-end: Java (Spring Boot framework for RESTful API).
• Database: MySQL or PostgreSQL.
• Authentication & Authorization: JWT (JSON Web Tokens) or Spring Security.
• Version Control: Git, GitHub (or GitLab, Bitbucket).

Testing Framework:

• Unit Testing: JUnit 5 (Java), Mockito (for mocking).
• Integration Testing: Spring Boot Test.
• UI Testing: Selenium or Cypress.
• API Testing: Postman or Rest Assured.
• Load Testing: JMeter

HANDWRITTEN DIGIT RECOGNITION USING MACHINE LEARNING

Developer

Overview:

This project uses machine learning algorithms to recognize handwritten digits (0-9). It’s a classic machine learning project that will help you learn how to work with image data.

Tools and Technologies:

• Python: For coding
• scikit-learn: For building machine learning models
• TensorFlow/Keras: For deep learning models (optional)
• Dataset: MNIST Dataset