By the end of the course, participants will be able to:
· Understand the basic concepts and principles of AI.
· Identify the various AI techniques and tools used in electrical engineering.
· Apply AI methods to solve complex electrical engineering problems.
· Evaluate the effectiveness of AI applications in real-world electrical engineering scenarios.
· Develop and implement AI models for specific electrical engineering tasks

· Electrical engineering students and professionals.
· Researchers and academics in the field of electrical engineering.
· Engineers interested in incorporating AI into their work.
· Technologists and data scientists focusing on electrical engineering applications

· Presentations by the course leader, including case examples.
· Group work on case studies - analysis, interaction, and discussion.
· Hands-on sessions with AI tools and software.
· Practical projects and assignments.

DAY 1: Introduction to AI and Machine Learning
· Overview of AI: History, Definitions, and Trends
· Basic Concepts of Machine Learning
· Supervised vs. Unsupervised Learning
· AI in Electrical Engineering: An Overview
· Case Study: AI in Power Systems

DAY 2: AI Techniques and Tools
· Neural Networks and Deep Learning
· Natural Language Processing (NLP)
· Reinforcement Learning
· AI Software and Tools (TensorFlow, Keras, etc.)
· Hands-on Session: Building a Simple Neural Network

DAY 3: AI Applications in Electrical Engineering I
· AI in Power Generation and Distribution
· Smart Grids and AI
· Predictive Maintenance using AI
· Case Study: AI in Renewable Energy Systems
· Group Activity: Analyzing AI Applications in Energy Sector

DAY 4: AI Applications in Electrical Engineering II
· AI in Signal Processing
· AI in Control Systems and Automation
· Robotics and AI in Electrical Engineering
· Case Study: AI in Electrical Vehicle Technology
· Guest Lecture: Industry Expert on AI in Electrical Engineering

DAY 5: Practical Implementation and Future Trends
· Developing and Implementing AI Models
· Ethical Considerations and Challenges in AI
· Future Trends and Innovations in AI and Electrical Engineering
· Group Project Presentations
· Course Review and Q&A Session

CDGA attendance certificate will be issued to all attendees completing minimum of 80% of the total course duration