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AI for Predictive Maintenance with Python
Welcome - Course Introduction
(Start Here) Introduction - Course Overview and Objectives
Course Structure
Course Material (PDF)
Introduction to Predictive Maintenance and Machine Learning
What is Predictive Maintenance?
Key Concepts in Predictive Maintenance
Introduction to Machine Learning
Machine Learning Techniques in Predictive Maintenance
Case Studies and Industry Examples
Quiz: Test Your Knowledge
Setting Up Your Coding Environment
Introduction to Jupyter Notebooks
Introduction to Google Colab
(Optional) Setting Up a Local Environment
(Optional) Introduction to Python for Machine Learning
Introduction to Programming
Introduction to Python
Functions
Lists
Loops
Collecting, Preparing and Analysing Your Data
Types of Data Used in Predictive Maintenance
Reading and Preparing Raw Data
Visualising Data
Extracting Features from Data in Time and Frequency Domains
Quiz: Test Your Knowledge
Hands-On Milestone Project: Prepare and Visualise Data
Predicting Equipment Failure with Machine Learning
Training Machine Learning Models to Detect Failure
Model Evaluation and Improvement
Training Deep Learning Models to Detect Failure
Quiz: Test Your Knowledge
Hands-On Milestone Project: Build a Failure Prediction Model
Anomaly Detection
Anomaly Detection Techniques
Quiz: Test Your Knowledge
Hands-On Milestone Project: Detecting Anomalies in Timeseries Data
Model Deployment and Monitoring
Best Practices for Deploying Predictive Maintenance Models
Deployment Case Study
Capstone Project: Build a Complete Predictive Maintenance Pipeline
From data cleaning to prediction on real engineering dataset
Conclusion and Next Steps
Recap of Key Concepts and Skills
Resources for Further Learning
Training Machine Learning Models to Detect Failure
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