Position: Software Engineer
Category: Python
English level: fluent
Years of experience: 1

ITLab - YeloBank Project: Selected as one of the 50 students from 5000 applicants for the ITLab - YeloBank project in Baku, Azerbaijan. Gained valuable experience working with Spring and Spring Boot frameworks. Connected multiple applications to a MySQL database, performed data manipulation, and interacted with REST APIs, showcasing strong backend development skills.

"ELACHI" Scholarship program winner: Elachi" Scholarship awarded for academic excellence in university and extra-curricular activities. This scholarship covered academic expenses for one academic year. Organized and conducted a 1-month Python training program for other scholarship recipients, demonstrating leadership and mentoring abilities while contributing to the academic community.
CodeMark Web Platform: Developed "CodeMark," a web-based interactive computing platform enabling users to write, run, and visualize JavaScript code in a Jupyter notebook-style environment. The platform allows easy creation and sharing of documents with live code, equations, and narrative text. Used HTML, CSS, JavaScript, React, esbuild, and WebAssembly to build this impressive web application.

Optimized "Foglie Dialloro" Website: Worked as a freelance Web Developer (Frontend) in Baku, Azerbaijan. Successfully optimized the "Foglie Dialloro" website, improving its performance by 70% according to Lighthouse metrics. This optimization likely led to enhanced user experience and search engine rankings.

TrainTyper SPA: Created a Single Page Application (SPA) called "TrainTyper" to test users' typing speed. Developed a custom text input field using vanilla JavaScript and implemented real-time typing speed calculations. Achieved a 100% performance diagnostics score on PageSpeed, demonstrating excellent web development and optimization abilities.

Heart Disease Prediction: Implemented the KNN algorithm from scratch in Python to predict heart disease. Utilized Python, NumPy, Scikit-learn, and Jupyter Notebook for data analysis and machine learning tasks. Through feature engineering, achieved similar accuracy compared to the Scikit-learn library.