12 June - 12 June, 2025
June 12 at 12:00 PM - 1:00 PM UTC+0
Event Start Time in your local time: (convert to other time zones?)
Webinar details
As power systems become increasingly complex with the integration of renewable energy, smart grids, and IoT technologies, vast amounts of data are continuously generated. This webinar will explore how big data and machine learning are transforming the energy sector by enabling real-time monitoring, predictive maintenance, demand forecasting, and optimization of energy distribution.
Attendees will gain insights into data collection, storage, and cleaning techniques, as well as advanced analytics methods applied to enhance reliability, efficiency, and sustainability in power networks. Real-world case studies and future trends, including AI-driven solutions and digital twins, will also be discussed, providing a practical understanding of how data-driven technologies are shaping the future of power engineering.
- The webinar will be recorded and will be sent out to registered attendees afterwards.
- A certificate of attendance will be provided to attendees who request one near the end of the live webinar session.
- Please note: the time stated on this event is in UTC. You will need to convert this to your own time zone.
Key takeaways from this webinar
- Understand the role of Big Data and Machine Learning in enhancing the efficiency, reliability, and sustainability of modern power systems.
- Learn about data lifecycle management in power networks, including best practices for data collection, cleaning, storage, and real-time analytics.
- Explore real-world applications and case studies showcasing predictive maintenance, demand forecasting, smart grid optimization, and the future of AI in power system management.
Related courses
This webinar/topic relates to the following schools of engineering Electrical Engineering and Industrial Automation, Instrumentation and Process Control is particularly found in the following courses:
- Professional Certificate of Competency in Big Data and Analytics in Electricity Grids
- Professional Certificate of Competency in Electrical Power System Protection
- 52886WA Advanced Diploma of Industrial Automation Engineering
- 52883WA Advanced Diploma of Applied Electrical Engineering (Electrical Systems)
- 52911WA Graduate Certificate in Internet of Things (loT) for Engineering (Foundations)
- Graduate Certificate in Industrial Automation and Machine Learning
About the presenter
Saeideh Sekhavat, EIT Lecturer
Saeideh Sekhavat (Sadie) is a Lecturer, Researcher, and IT professional with a strong background in mathematics and a focus on applying artificial intelligence in healthcare. She holds a bachelor’s degree in Applied Mathematics and a graduate degree in Systems Analysis from the National University of Singapore. Her experience includes the use of AI tools and deep learning techniques for medical image processing and analysis to support healthcare applications. Sadie has also been involved in projects related to data analysis, mathematical modeling, and computational image analysis. She is currently working as a full-time lecturer at the Engineering Institute of Technology (EIT), where she is passionate about delivering practical, industry-focused education.