I’m Tolga Değirmenci, a Computer Engineering graduate focused on becoming a Data Scientist. I develop myself in data analysis, machine learning, AI-powered analytics, business intelligence, and end-to-end data-driven solutions.
Python · SQL · Pandas · NumPy · Scikit-learn · Power BI · Machine Learning · GitHub
I am focused on becoming a Data Scientist by improving my skills in data analysis, statistical thinking, machine learning, model evaluation, feature engineering, and AI-powered analytics.
I combine data analysis, machine learning, business intelligence, and software development to transform complex datasets into clear insights and practical AI-powered solutions. I am currently based in Istanbul, Türkiye.
I work with Python, SQL, Pandas, NumPy, Excel, and Power BI to clean, analyze, visualize, and interpret data for business and technical use cases.
I develop myself in supervised learning, model evaluation, feature engineering, computer vision, Scikit-learn, TensorFlow, and YOLO-based projects.
I am interested in building AI-supported data products, analytical agents, intelligent pipelines, and decision-support systems with real business value.
Internship experience across business intelligence, data warehousing, MIS, and machine learning engineering.
Designed dynamic Power BI dashboards, optimized SQL queries, extracted business insights, and automated reporting pipelines. This experience strengthened my analytical thinking and understanding of business data.
Produced analytical dashboards for executive decision-making and collaborated with cross-functional teams to translate business requirements into data-driven reports.
Worked with Microsoft Power Platform tools, SQL Server-based BI solutions, and Power BI dashboards connected to SQL data pipelines.
Explored deep learning methods with Vision Transformers and trained CNN models for image classification, building a foundation in machine learning and computer vision.
AI agents, analytical pipelines, computer vision systems, and full-stack projects with data-driven components.
End-to-end AI pipeline that analyzes a YouTube music video URL, identifies the artist, retrieves album information, processes lyrics, and generates token-level analytics.
Real-time surveillance system using deep learning to detect suspicious behavior, process video streams, and send alerts through a Firebase-connected mobile app.
Community-driven gaming website where users can rate, review, and discuss games using a modern full-stack architecture.
Tools and technologies I use while developing myself in data science, machine learning, analytics, BI, and AI-powered projects.
Coursework included Artificial Intelligence, Machine Learning, Deep Learning, Applied AI, Computer Vision, AWS, Data Structures, Database Systems, Microprocessors, and IoT.
Completed high school education with a strong foundation in analytical thinking, mathematics, and science-oriented learning.
I am open to opportunities in Data Science, Machine Learning, AI-powered analytics, and data-driven software projects.
tolgadegirmenci4@gmail.com