• views: 139
• date: 2 May 2026
• posted by: 0nelove

From beginners to advanced level on AI-ML with Solved Numerical and MATLAB examples
What you'll learn
Understand basics of Artificial Neural Networks and Machine Learning
Understand and develop different Learning rules Regression and Classification models
Apply Machine Learning Models to Electrical Engineering Problems
Hand-on training on MATLAB platform for Electrical Engineers
Requirements
No programming needed as prerequisite.
Basics about Electrical Engineering
Description
AI & ML for Electrical Engineers: Theory & Hands-on
This course provides a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) with a strong focus on applications in Electrical Engineering. It is designed for students, researchers, and professionals who want to integrate intelligent techniques into modern power and energy systems.
The course begins with the fundamentals of Artificial Neural Networks (ANNs), including neuron models, activation functions, architectures, and learning mechanisms. You will explore key concepts such as gradient descent, loss functions, and learning rules, building a solid theoretical foundation.
Moving forward, the course covers advanced ANN paradigms and ML algorithms, including backpropagation, radial basis function networks, self-organizing maps, and functional link networks. You will also learn essential regression, clustering, and classification techniques, enabling you to analyze complex datasets effectively.
A key highlight of this course is its hands-on MATLAB implementation, where you will work on real-world electrical engineering problems such as
Transformer efficiency prediction
Load forecasting and classification
Bus voltage estimation
Fault diagnosis in electrical machines
By the end of this course, the learners will gain expert level knowledge and will be able to design, implement, and evaluate AI/ML models for practical electrical engineering applications, making them industry-ready for smart grids and intelligent energy systems.
Who this course is for
Undergraduate and Postgraduate Student of Electrical and Electronics Engineering
Ph.D. Scholars and Researchers working in the domain of Electrical Engineering
Industry professionals and AI-ML researchers



   
   
   

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