Hello! My name is Emircan Güneş.

I took part in a website development project and was responsible for creating the front-end part of the project. Using HTML, CSS, and JavaScript, I successfully completed the front-end of a game sales website. On this website, users can perform actions such as purchasing games, adding them to the cart, signing up, logging in, and viewing purchased games in their library.

As part of our graduation project YKS Analysis, we developed a comprehensive web-based platform that analyzes and predicts university placement data in Turkey. In the frontend development, I used React and Material UI to design responsive and interactive interfaces tailored for different user types: students, university administrators, and the Higher Education Council (YÖK). I also collected data from the YÖK Atlas API using Python’s Scrapy library and organized it within a MySQL database. In the machine learning component, I experimented with several algorithms and implemented the most accurate one, XGBoost, using Python. By utilizing historical data, our model was able to make predictions for university rankings and placement probabilities for the year 2025. Additionally, we used Python libraries to generate visualizations that enabled users to analyze the data more effectively and intuitively.

In this project, I developed an application that can manage patient reports and patient information from laboratories using the React library and JSON Server. With this application, you can add reports, sort them by date, search using the search bar, and update them.

For the Database course at the university, my friends and I completed a project together. After identifying a problem, we systematically prepared the stages of the database to solve this problem. We worked using Microsoft SQL. At the end of the project, I developed an interface to manage the database, while my friends worked on the back-end part.

Together with my friends, we trained an artificial intelligence model using a dataset from Kaggle that contains symptoms and values related to diseases. We used Python for model training and compared the results of different algorithms to select the best-performing one. Finally, we developed an interface that allows users to select symptoms and calculate the probabilities of possible diseases.

I created my first website using Bootstrap. Later, I discovered the Bootstrap Studio application. I tried to learn by preparing templates through this application and improved myself in using Bootstrap.