AIML in Engineering Course
Gain expertise in applying AIML to engineering challenges using real-world pump sensor data. Master sensor physics, feature engineering, time-series predictive models, deployment strategies, and root cause analysis to reduce downtime, boost reliability, and drive data-informed engineering decisions in industrial settings.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This course teaches how to transform raw sensor data into actionable predictive maintenance insights for engineering applications. Delve into pump operations, common failure patterns, feature extraction techniques, time-series forecasting models, and rigorous model assessment methods suited for operational environments. Additionally, explore model deployment, risk assessment, explainability tools, and root cause investigations to create effective, proven AIML systems that enhance equipment availability and lower maintenance expenses.
Elevify advantages
Develop skills
- Deploy reliable AIML models in industrial plants facing noise, data drift, and limited failure data.
- Engineer key features from sensor data for pump health using time, frequency, and multi-sensor analysis.
- Develop and validate predictive maintenance models with time-series aware evaluation techniques.
- Convert model predictions into actionable maintenance plans, alerts, and engineering choices.
- Conduct clear root cause analysis connecting ML features to actual equipment failures.
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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