On April 21, 2024, the Department of Electrical and Electronic Engineering (EEE), Faculty of Engineering (FE), AIUB, hosted a workshop, titled “Machine Learning: An Essential Tool for Forecasting Renewable Power Generation”. The workshop started at 6:00 PM with over 40 graduate and undergraduate students from the Faculty of Engineering. The workshop aimed to investigate how machine learning methods can be integrated and used in practice to anticipate the production of renewable energy and increase efficiency.

Dr. Mohammad Nasir Uddin (Senior Associate Professor & Head [Graduate Program], Department of EEE, Faculty of Engineering, AIUB) facilitated and inaugurated the session. After the commencement ceremony, the session was addressed by Dr. Shameem Ahmad (Assistant Professor, Department of EEE, Faculty of Engineering, AIUB). During the event, Dr. Shameem delved into the foundational concepts and practical applications of machine learning, distinguishing between various forms of artificial intelligence, and elucidating the nuances between deep learning and machine learning. He underscored the importance of understanding essential software tools like Python, Jupyter Notebook and Anaconda for executing machine learning projects, demonstrating their utility firsthand. Dr. Shameem then elucidated data processing strategies and emphasized the significance of dataset preparation for enhancing model performance, while also spotlighting key libraries commonly employed in machine learning tasks. He proceeded to outline the step-by-step process of developing, training, and testing machine learning models, culminating in real-world applications that showcased the tangible impact and insights garnered from predictive models. The workshop was concluded by Dr. Mohammad Nasir Uddin, with the closing remarks and a token of appreciation given to the speaker as a gesture of thanks after the session.

The event effectively demonstrated machine learning's broad range of applications across renewable energy and emphasized its relevance. Additionally, it gave participants an overview of machine learning and its useful applications in sustainable power development. These features make the workshop compliant with several Sustainable Development Goals (SDGs), such as SDG 9 (Industry, Innovation, and Infrastructure) and SDG 4 (Quality Education).