Transform Your Career and Workplace

Predictive maintenance isn’t just about fixing machines before they break—it’s about rethinking how you work, innovate, and lead in your field. In this hands-on course, you'll master AI-driven techniques to streamline operations, reduce costs, and drive smarter decision-making in your workplace.

By the end of this course, you will:

  • Think like a data-driven problem solver: learn how to identify, frame, and tackle predictive maintenance challenges using machine learning.
  • Build practical, job-ready skills: gain hands-on experience in preparing data, training machine learning models and creating portfolio-worthy projects.
  • Boost your career potential: stand out by mastering a sought-after skill set that bridges engineering and AI.
  • Solve real problems, faster: discover how to apply machine learning to minimize downtime, reduce costs, and implement smarter maintenance strategies.
  • Gain confidence in AI: whether you’re a beginner or looking to deepen your expertise, this course breaks down complex concepts into actionable steps.



WHAT YOU WILL LEARN

What predictive maintenance is




How to prepare and analyse your data




How to predict equipment failure and detect anomalies with machine learning


Curriculum Sneak Peek

  Welcome - Course Introduction
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  Introduction to Predictive Maintenance and Machine Learning
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  Setting Up Your Coding Environment
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  (Optional) Introduction to Python for Machine Learning
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  Collecting, Preparing and Analysing Your Data
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  Predicting Equipment Failure with Machine Learning
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  Anomaly Detection
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  Model Deployment and Monitoring
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  Capstone Project: Build a Complete Predictive Maintenance Pipeline
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  Conclusion and Next Steps
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COURSE STRUCTURE

Pre-Recorded Video Lessons


Hands-On Exercises and Quizzes


Capstone Project


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Frequently Asked Questions

1. Are there any prerequisites?

  • An internet connection to access a coding environment and course lectures.
  • Some Python experience is beneficial, but not required. An optional Python crash course is offered with the course.

2. Are there any hardware requirements?

  • Desktop or laptop computer capable of running the latest version of Chrome or Firefox.

3. Is there a refund policy?

  • A money-back guarantee is offered for 14 days from purchase. After this date, refunds will not be provided.
  • If purchasing the course on pre-release, refunds will be offered for 14 days from release date.

4. Is the course beginner-friendly?

  • Yes, the course is designed for learners of all levels. Complex concepts are broken down, and step-by-step guidance is provided for practical exercises.