Statement of Reasons
(Application for the M.Sc. in Data Science - TUM)
Dear Admission Committee,
As a recent graduate of Yıldız Technical University's Computer Engineering program in Istanbul, Turkey, I am applying to the Master of Science in Data Science and Statistics at the Technical University of Munich (TUM). My academic record demonstrates strong commitment, having completed my full degree requirements (240 ECTS credits) in 7 semesters instead of the standard 8. This accelerated completion reflects both my academic capabilities and my eagerness to advance to specialized graduate studies in the data science field.
Three different internship experiences where I had the opportunity to put the theoretical knowledge I acquired during my academic education into practice have embodied my interest in the field of data science. During my sophomore summer vacation, I worked with technologies such as Angular, .NET, TypeScript and Docker in my internships at Log Bilgisayar and Arge24 companies, and experienced real-life applications of backend, frontend and database integration. During my junior summer vacation, I had the opportunity to work with the Software Architects team at the global consultancy firm OBSS. Here, I further developed my frontend development skills by working on component-based design and responsive interfaces in web applications.
My most significant experience with data science came during my third undergraduate year, when I joined a TUBITAK-funded research project titled "Ocular Sperm Analysis," supervised by Prof. Dr. xxxxx yyyyy. While the broader project involved more than ten undergraduate and graduate students working on related biomedical AI problems, I independently carried out a subproject focused on building a diagnostic assistant application for medical professionals and data labelers.
Over the course of a year, I developed and evaluated deep learning models to detect and classify sperm cells in ocular microscope images. For the object detection stage, I trained models using YOLOv8 across multiple datasets, measuring performance with detailed metrics such as Train/Val box loss, class loss, distribution focal loss, mAP@50, and mAP@50-95. I then implemented classification models to identify the location and type of morphological deformities, using metrics including precision, recall, F1-score, support, and overall accuracy. In total, I trained and analyzed over 1000 models, systematically comparing different architectures, datasets, and hyperparameter configurations.
All work was conducted autonomously, with only monthly meetings for feedback and reporting. I wrote regular literature reviews and comprehensive experiment reports, documenting both the successes and limitations of each approach. At the end of the project, I wrote an academic-style thesis based on my findings, which served as my undergraduate graduation project. Although it was not formally published, the process of writing and structuring the thesis in a scientific format significantly improved my ability to communicate technical work. My supervisor expressed strong satisfaction with my work and is fully willing to provide a reference if needed. This experience not only strengthened my practical skills in machine learning, model evaluation, and research communication, but also deepened my passion for data-driven biomedical innovation. It confirmed my motivation to pursue graduate-level studies in Data Science, where I can further develop my analytical skills and contribute to impactful, interdisciplinary projects.
I have been working at Turkish Technology, the technology subsidiary of Turkish Airlines, since January 2025. During this time, I closed critical security vulnerabilities in large-scale enterprise applications, took part in the integration of new features, and gained experience in unit test development. In addition, I gained an important perspective on work discipline, team responsibility sharing, and enterprise software development processes in large companies.
Working with sprint structures and project management tools based on agile methodologies strengthened my team communication and work tracking skills. In this way, I developed not only my technical but also my professional business life competencies. While my current position is in full-stack development, working in complex systems has given me firsthand exposure to data flows, backend logic, and deployment processes. Over time, I became increasingly interested in how data drives decision-making and system optimization. This realization inspired me to pursue academic specialization in data science, where I aim to combine my engineering background with a more analytical perspective and contribute to data-driven innovation.
I haven't written the conclusion part yet. What do you think? About my eligibility and overall this letter. I am waiting for your comments to improve this letter.
(Application for the M.Sc. in Data Science - TUM)
Dear Admission Committee,
As a recent graduate of Yıldız Technical University's Computer Engineering program in Istanbul, Turkey, I am applying to the Master of Science in Data Science and Statistics at the Technical University of Munich (TUM). My academic record demonstrates strong commitment, having completed my full degree requirements (240 ECTS credits) in 7 semesters instead of the standard 8. This accelerated completion reflects both my academic capabilities and my eagerness to advance to specialized graduate studies in the data science field.
Three different internship experiences where I had the opportunity to put the theoretical knowledge I acquired during my academic education into practice have embodied my interest in the field of data science. During my sophomore summer vacation, I worked with technologies such as Angular, .NET, TypeScript and Docker in my internships at Log Bilgisayar and Arge24 companies, and experienced real-life applications of backend, frontend and database integration. During my junior summer vacation, I had the opportunity to work with the Software Architects team at the global consultancy firm OBSS. Here, I further developed my frontend development skills by working on component-based design and responsive interfaces in web applications.
My most significant experience with data science came during my third undergraduate year, when I joined a TUBITAK-funded research project titled "Ocular Sperm Analysis," supervised by Prof. Dr. xxxxx yyyyy. While the broader project involved more than ten undergraduate and graduate students working on related biomedical AI problems, I independently carried out a subproject focused on building a diagnostic assistant application for medical professionals and data labelers.
Over the course of a year, I developed and evaluated deep learning models to detect and classify sperm cells in ocular microscope images. For the object detection stage, I trained models using YOLOv8 across multiple datasets, measuring performance with detailed metrics such as Train/Val box loss, class loss, distribution focal loss, mAP@50, and mAP@50-95. I then implemented classification models to identify the location and type of morphological deformities, using metrics including precision, recall, F1-score, support, and overall accuracy. In total, I trained and analyzed over 1000 models, systematically comparing different architectures, datasets, and hyperparameter configurations.
All work was conducted autonomously, with only monthly meetings for feedback and reporting. I wrote regular literature reviews and comprehensive experiment reports, documenting both the successes and limitations of each approach. At the end of the project, I wrote an academic-style thesis based on my findings, which served as my undergraduate graduation project. Although it was not formally published, the process of writing and structuring the thesis in a scientific format significantly improved my ability to communicate technical work. My supervisor expressed strong satisfaction with my work and is fully willing to provide a reference if needed. This experience not only strengthened my practical skills in machine learning, model evaluation, and research communication, but also deepened my passion for data-driven biomedical innovation. It confirmed my motivation to pursue graduate-level studies in Data Science, where I can further develop my analytical skills and contribute to impactful, interdisciplinary projects.
I have been working at Turkish Technology, the technology subsidiary of Turkish Airlines, since January 2025. During this time, I closed critical security vulnerabilities in large-scale enterprise applications, took part in the integration of new features, and gained experience in unit test development. In addition, I gained an important perspective on work discipline, team responsibility sharing, and enterprise software development processes in large companies.
Working with sprint structures and project management tools based on agile methodologies strengthened my team communication and work tracking skills. In this way, I developed not only my technical but also my professional business life competencies. While my current position is in full-stack development, working in complex systems has given me firsthand exposure to data flows, backend logic, and deployment processes. Over time, I became increasingly interested in how data drives decision-making and system optimization. This realization inspired me to pursue academic specialization in data science, where I aim to combine my engineering background with a more analytical perspective and contribute to data-driven innovation.
I haven't written the conclusion part yet. What do you think? About my eligibility and overall this letter. I am waiting for your comments to improve this letter.
