CODE: PE15
DURATION: 5 Days/10 Days
CERTIFICATIONS: CPD
This course offers a detailed study of AI-driven models and predictive analytics for energy systems. Participants will learn how to forecast system behavior, optimize grid operations, improve asset performance, and prevent failures proactively. The curriculum covers machine learning algorithms, neural networks, and big data tools applied to energy challenges. Through theory and case studies, delegates will develop skills to implement AI strategies, integrate smart sensors and IoT platforms, and create predictive models that enhance reliability, sustainability, and cost efficiency in the energy sector.
This course is available in the following formats:
Virtual
Classroom
Request this course in a different delivery format.
Course Outcomes
Delegates will gain the knowledge and skills to:
Apply machine learning techniques for load forecasting and demand prediction.
Develop predictive maintenance models for electrical assets using real-time data.
Use data analytics tools to identify and diagnose anomalies in grid performance.
Implement intelligent fault detection and self-healing network strategies.
Analyze large datasets from SCADA, PMU, and smart meter systems for operational insights.
Evaluate cybersecurity and ethical considerations in AI-based grid management.
At the end of this course, you’ll understand:
This course is designed for power system engineers, data analysts, operations managers, reliability engineers, AI practitioners, digital transformation officers, and energy technology innovators who want to apply data analytics and machine learning tools to power system management. It is equally valuable for utility professionals, regulatory bodies, academic researchers, and consultants seeking to modernize power operations through digital intelligence and predictive analytics.
✓ Modern facilities
✓ Course materials and certificate
✓ Accredited international trainers
✓ Training materials and workbook
✓ Access to online resources
