| Attribute | Detail |
|---|---|
| Format | Online, self-paced course |
| Level | Basic / Beginner |
| Duration | 2–3 Weeks |
| Certification | e-Certification |
| Fee | ₹199 / $20 |
| Tools | Predictive Maintenance Data Analysis Sensor Data Condition Monitoring Failure Prediction |
About the Predictive Maintenance: Basics Course
The Predictive Maintenance: Basics course is a free, beginner-friendly self-paced program designed to introduce learners to how data and machine learning are used to predict equipment failures before they occur.
The course explains how industries monitor machines, analyze performance data, and use predictive techniques to reduce downtime and maintenance costs. Learners will explore concepts such as condition monitoring, failure prediction, and data-driven maintenance strategies. This course is ideal for beginners interested in industrial applications of AI, IoT, and data analytics.
Program Highlights
• Free beginner-level predictive maintenance course
• Online self-paced learning format
• Simple explanation of maintenance and prediction concepts
• Covers equipment monitoring and failure prediction basics
• Real-world examples from manufacturing and industry
• Suitable for students and first-time learners
• e-Certification upon successful completion
Course Curriculum
Module 1: Introduction to Predictive Maintenance
- What is Predictive Maintenance?
- Types of Maintenance: Reactive, Preventive, and Predictive
- Importance of Maintenance in Industry
- Applications of Predictive Maintenance
Module 2: Data in Maintenance Systems
- Types of Machine and Sensor Data
- Introduction to Condition Monitoring
- Understanding Equipment Performance Data
- Importance of Data Quality
Module 3: Basic Predictive Techniques
- Introduction to Failure Prediction
- Identifying Patterns and Anomalies
- Simple Data Analysis for Maintenance
- Examples of Predictive Maintenance Use Cases
Module 4: Benefits and Challenges
- Advantages of Predictive Maintenance
- Reducing Downtime and Costs
- Challenges in Implementation
- Limitations of Prediction Models
Module 5: Applications and Future Scope
- Predictive Maintenance in Manufacturing, Energy, and Transportation
- Role of AI and IoT in Smart Maintenance
- Career Opportunities in Industrial AI and Analytics
- Mini Learning Activity / Concept-Based Practice
Tools, Techniques, or Platforms Covered
Predictive Maintenance Data Analysis Sensor Data Condition Monitoring Failure Prediction
Real-World Applications
- Predicting machine failures in manufacturing plants
- Monitoring equipment performance using sensor data
- Reducing downtime in industrial operations
- Improving maintenance planning and efficiency
- Supporting smart factories and Industry 4.0 systems
Who Should Attend & Prerequisites
- This course is suitable for students, beginners, engineers, technicians, and professionals interested in industrial applications of AI and data analytics.
- It is also useful for learners from mechanical, electrical, industrial engineering, manufacturing, and technology backgrounds.
Certification
