Munich, Bavaria, Germany
Electrical and Electronics Engineering graduate, currently working as an Intern Data Analyst. With a strong educational background and growing experience in data analysis and machine learning, I am highly motivated to apply my knowledge and skills to address engineering challenges.
Currently enrolled in a comprehensive program covering advanced data analytics concepts, including machine learning, statistics, and regression analysis. Improving skills in Python programming, predictive modeling and data analysis.
> Analyzing various optical network data for network optimization purposes. > Implemented machine learning algorithms such as Random Forests and Variational Autoencoders as well as time series models such as Autoregression, Moving Average, ARIMA, and Prophet. > Used Python with libraries such as Pandas, Keras, Matplotlib, Numpy, and Statsmodel for data analysis and model development. > Gained basic knowledge of optical networks, developed problem-solving skills and enhanced analytical thinking by interpreting complex data patterns and trends.
Conducted an in-depth study on convolutional neural networks (CNN) and analyzed the effects of model’s parameters on its performance. Developed models using Python and deep learning frameworks such as TensorFlow and Keras. Authored a conference paper detailing the research findings and methodologies.
Participated in a blockchain based project: EsOguChain, a digital student certificate application. Gained knowledge about blockchain technology and contributed to writing and reviewing Python code for the application’s API. Co-authored an article detailing the project and its applications.
Gained basic knowledge about telecommunication and data networks. Experienced the process of infrastructure setup and troubleshooting.