AIML in Engineering Course
Gain expertise in AI/ML for engineering using authentic pump datasets. Delve into sensor mechanics, feature creation, predictive maintenance modelling, implementation techniques, and root-cause investigations to minimise downtime, enhance dependability, and leverage facility data for assured engineering choices.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This course teaches how to convert raw sensor data into dependable predictive maintenance decisions for engineering applications. You'll explore pump basics, failure patterns, feature engineering, time-series analysis, and model assessment suited to actual industrial sites. It also includes deployment strategies, risk handling, model interpretability, and root cause investigations to create effective, verified AI/ML systems that boost equipment availability and reduce servicing expenses.
Elevify advantages
Develop skills
- Deploy resilient AI/ML models in industrial settings despite noise, data drift, and limited failure data.
- Design sensor features for pump condition monitoring with time, frequency, and multi-sensor inputs.
- Develop and test predictive maintenance models using time-sensitive validation methods.
- Convert model predictions into actionable maintenance plans, notifications, and engineering choices.
- Conduct clear root cause analysis connecting ML features to physical equipment faults.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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