Programme Parameters
Graduate / Intermediate
4 Weeks (40 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
AI in Manufacturing and Industry 4.0 shows how machine learning is transforming production into the smart, connected factory. You learn to apply AI to the core problems of modern manufacturing: predictive maintenance that prevents downtime, computer-vision quality inspection that catches defects, and process optimisation that raises yield and cuts waste. The course sets these within the Industry 4.0 vision — sensors, IIoT, digital threads and data-driven operations — and the practicalities of deploying AI on the factory floor. You finish able to apply AI to a real manufacturing problem. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This course covers AI in manufacturing and Industry 4.0 — predictive maintenance, quality inspection, process optimisation and the smart, connected factory.
📋 Course Objectives
1. Build predictive-maintenance models for equipment.
2. Apply computer vision to quality inspection.
3. Optimise processes for yield and efficiency.
4. Work with IIoT and sensor data.
5. Connect AI to the Industry 4.0 factory.
👥 Who Should Enroll?
• Manufacturing and process engineers
• Industrial data scientists
• Operations and quality professionals
• Students of smart manufacturing
🚀 Key Learning Outcomes
• The ability to apply AI in manufacturing.
• A predictive-maintenance or inspection project.
• An Industry 4.0 operations perspective.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Module 1 — Foundations of AI in Manufacturing and Industry 4.0
Introduction to Industry 4.0 and smart manufacturing • Evolution from conventional to intelligent production systems • Role of AI in industrial transformation • Core pillars: automation, connectivity, data, and intelligence
Module 2 — Industrial Data, IoT, and Connected Systems
Industrial data sources (Sensors, PLCs, SCADA) • IoT-enabled systems and data acquisition frameworks • Data integration and communication frameworks • Challenges in industrial data quality and real-time monitoring
Module 3 — AI and Machine Learning for Industrial Applications
Fundamentals of AI, ML, and Deep Learning in industry • Supervised, unsupervised, and reinforcement learning • Classification, regression, and anomaly detection • Model performance evaluation in manufacturing
Module 4 — Predictive Maintenance and Condition Monitoring
Principles of predictive maintenance and asset health • Sensor-driven fault detection and failure prediction • AI models for maintenance planning and downtime reduction • Applications in machinery and equipment systems
Module 5 — Computer Vision and Intelligent Quality Control
Computer vision in inspection and defect detection • Visual quality assurance and deep learning analysis • Automated quality control in production environments
Module 6 — Process Optimization, Robotics, and Automation
AI-driven process optimization and production planning • Resource allocation, scheduling, and throughput enhancement • Intelligent robotics and human-machine collaboration (Cobots)
Module 7 — Digital Twins, Edge AI, and Industrial Deployment
Introduction to digital twins and edge computing • Real-time industrial AI and cloud-edge integration • Challenges: Scalability, latency, and cybersecurity
Module 8 — Applications, Case Studies, and Future Trends
Case studies in predictive maintenance and quality inspection • Smart factory examples and workflow optimization • Future trends: Generative AI and sustainable manufacturing
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Additive Manufacturing |
| Covered Tool / Platform | AI in Manufacturing |
| Covered Tool / Platform | AI-Driven Innovation |
| Covered Tool / Platform | Autonomous Robots |
| Covered Tool / Platform | Cyber-Physical Systems |
Frequently Asked Questions
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