Module 1 – Introduction to AI & Machine Learning

• AI fundamentals and applications in ECE
• Machine Learning concepts
• Supervised, Unsupervised & Reinforcement Learning
• Python basics for AI
• NumPy, Pandas and Matplotlib

Module 2 – Machine Learning for ECE

• Data preprocessing
• Regression and Classification
• Decision Trees and Random Forest
• K-Means Clustering
• Model evaluation and accuracy
• Feature engineering

Module 3 – AI for Signal Processing

• Digital signals and datasets
• Signal classification using ML
• Noise detection and removal
• Feature extraction
• Audio and speech signal analysis
• Anomaly detection

Module 4 – AI & Embedded Systems

• Introduction to Embedded AI
• Microcontrollers and AI
• Sensors and data collection
• Edge AI concepts
• Arduino/Raspberry Pi applications
• AI-based sensor monitoring

Module 5 – AI for IoT & Communication

• AI + IoT architecture
• Smart sensor systems
• Wireless communication data analysis
• 5G and AI
• Network anomaly detection
• Predictive maintenance

Module 6 – Deep Learning & Computer Vision

• Neural Networks fundamentals
• CNN concepts
• Image classification
• Object detection basics
• TensorFlow/Keras introduction
• AI-based electronic component inspection

Module 7 – Generative AI & Modern ECE Applications

• Generative AI fundamentals
• Large Language Models overview
• AI-assisted electronics design
• AI for circuit analysis
• AI-based troubleshooting
• Prompt engineering for engineering applications

Module 8 – Practical Projects

• Smart sensor fault detection
• AI-based signal classifier
• Electronic component image classifier
• IoT predictive maintenance system
• AI-based communication/network anomaly detector
• Mini ECE + AI project