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Explore how artificial intelligence is transforming the renewable energy transition, from data fundamentals to applications. Gain practical insight into neural networks, deep learning, forecasting, optimisation and predictive maintenance, supported by case studies shaping power systems. This course introduces renewable energy trends alongside concepts in data, digitalisation and AI. You will learn methods, with emphasis on neural networks and deep learning, then apply them to challenges such as load forecasting, predictive maintenance, and network control and optimisation. It concludes with AI's energy impact and research directions.
Explore how artificial intelligence is transforming the renewable energy transition, from data fundamentals to applications. Gain practical insight into neural networks, deep learning, forecasting, optimisation and predictive maintenance, supported by case studies shaping power systems. This course introduces renewable energy trends alongside concepts in data, digitalisation and AI. You will learn methods, with emphasis on neural networks and deep learning, then apply them to challenges such as load forecasting, predictive maintenance, and network control and optimisation. It concludes with AI's energy impact and research directions.
This course is suited to renewable energy professionals, engineers, and managers seeking to understand how AI supports the energy transition. It's also valuable for data analysts, software specialists, researchers, and students interested in AI-driven forecasting, optimisation, and energy systems.
Upon successful completion, you'll receive industry-recognised certifications that validate your expertise and boost your credibility with employers.
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