By the end of this program, participants will be able to:

• Apply AI and ML techniques to predictive maintenance.
• Collect, clean, and analyze industrial sensor data.
• Build and evaluate predictive models for equipment failure.
• Integrate AI insights into maintenance operations.
• Assess ROI and future trends in AI-driven maintenance.

1. Predictive Maintenance Concepts and AI Fundamentals
2. Industrial Data Collection, Cleaning, and Preprocessing
3. Feature Engineering and Visualization Techniques
4. Machine Learning Models for Fault Detection and Prediction
5. Time Series and Anomaly Detection for Condition Monitoring
6. AI Model Deployment and Integration with SCADA Systems
7. Maintenance Optimization and ROI Analysis
8. Capstone Project: Predictive Maintenance Framework