- Dataset preparation for AI models.- Implementing AI solutions using Python and machine learning frameworks (such as TensorFlow, PyTorch, or scikit-learn).- Building experimental design for new projects.- Optimize and fine-tune AI models for performance, scalability, and accuracy.- Deploy AI models into production environments, ensuring stability, reliability, and security.- Monitor and evaluate the performance of deployed models, and iterate on improvements.- Document and communicate AI solutions, methodologies, and best practices to technical and non-technical stakeholders.

- Leading the development and execution of the AI roadmap, aligning with business goals to improve product capabilities and operational efficiency.- Overseeing multiple AI/ML projects from concept to deployment, ensuring on-time delivery and maintaining high standards of performance and accuracy.- Driving AI innovation by researching and implementing state-of-the-art algorithms and technologies to solve complex business problems and introduce new product features.- Working closely with stakeholders across different departments to ensure AI initiatives meet business needs and are integrated seamlessly into existing workflows.- Leveraging expertise in machine learning, natural language processing (NLP), computer vision, and deep learning to guide the development of AI models, ensuring they are robust, scalable, and optimized for production.

- Testing the websites whether the software works correctly and actively on the end user side by performing E2E and UI tests with Cypress.- Creating the Q/A Scenarios documentation for multiple apps.- Providing the test automation to run in parallel on different browsers at certain times of the day by creating a pipeline for Cypress tests and setting a schedule.

- Implementing the dataset for MASK R-CNN and YOLOv8 models.- Analyzing image datasets and comparing the results by implementing different metrics using Python.- Performing the result performance analysis of the models trained with the original dataset and the augmented dataset.

Assistant student to Assoc. Prof. Dr. Caner Özcan in computer laboratory sessions of Programming Languages I, Programming Languages II, and Introduction to Machine Learning lectures to make students well informed on algorithm development, C programming language, machine learning, and Python programming language.

Various applications in machine learning and deep learning were realized using Python language. In addition, studies were carried out on topics such as data science and data analysis.

I voluntarily have done research and development work about data science, machine learning, deep learning, computer vision, and image processing under the supervision of Assoc. Prof. Dr. Caner Özcan.