Mentor Based
Industry 5.0: Hands-on AI in Manufacturing
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Course Overview
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Industry 5.0: Hands-on AI in Manufacturing
Professional Certification Program
π₯
FormatLive + Recorded
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Duration8 Weeks
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CertificationVerified
Program Syllabus
Module 1
About This Course
Join the Industry 5.0: Hands-on AI in Manufacturing workshop to explore AI applications in predictive maintenance, process optimization, and robotics. Over three days, gain practical experience using tools like Google Colab, TensorFlow, and OpenAI Gym. Learn to build AI models for real-world manufacturing challenges and collaborate on sustainable, AI-driven solutions.
Module 2
Aim
The workshop aims to equip participants with practical AI skills for predictive maintenance, process optimization, robotics, and sustainability, enabling them to tackle real-world manufacturing challenges and drive innovation in Industry 5.0.
Module 3
Workshop Objectives
- Train in AI tools like Google Colab and TensorFlow for manufacturing.
- Build predictive maintenance models.
- Optimize processes using reinforcement learning.
- Design AI-driven robotics for automation.
- Apply AI for resource optimization and sustainability.
- Collaborate on AI-driven manufacturing projects.
Module 4
Workshop Structure
Module 5
Day 1: Foundations of AI in Manufacturing and Predictive Maintenance
- Google Colab Setup: Get started with Google Colab and learn the basics of Python programming for AI tasks.
- Python for AI: Introduction to essential libraries like Pandas, NumPy, and Scikit-learn for data manipulation and machine learning tasks.
- Predictive Maintenance: Learn how to build a predictive maintenance model using real-world data (e.g., machine sensor data) to predict equipment failures.
- Data Visualization: Visualize your data and model performance using Matplotlib and Seaborn.
π οΈ Hands-on Tools:
- Setup Google Colab for coding and model execution.
- Load and preprocess sensor data using Pandas.
- Build a predictive maintenance model using logistic regression or decision trees.
Module 6
Day 2: AI for Process Optimization, Robotics, and Quality Control
- Reinforcement Learning for Process Optimization: Learn the fundamentals of reinforcement learning using OpenAI Gym to optimize manufacturing processes like energy use and production throughput.
- AI-Powered Robotics: Build an AI model to simulate a robotics system that can navigate a manufacturing floor or handle sorting tasks.
- Machine Vision for Defect Detection: Build a Convolutional Neural Network (CNN) to detect defects in products and optimize quality control.
π οΈ Hands-on Tools:
- Set up a reinforcement learning environment with OpenAI Gym to optimize a manufacturing process.
- Implement an autonomous robot simulation using reinforcement learning.
- Train a CNN using TensorFlow to classify defective products.
Module 7
Day 3: AI for Autonomous Systems, Sustainability, and Collaborative Projects
- Building Autonomous Systems: Learn how to implement autonomous robots using reinforcement learning for real-time decision-making in manufacturing tasks.
- AI for Sustainability: Explore how AI can optimize resource usage, reduce waste, and promote sustainable practices in manufacturing.
- Collaborative Research Project: Apply all the learned skills to a real-world manufacturing problem, working in teams to develop AI-driven solutions.
π οΈ Hands-on Tools:
- Implement an autonomous robot using Deep Q-Learning (DQN) in Google Colab.
- Build an AI model to optimize resource allocation and reduce carbon footprint in manufacturing processes.
- Group Challenge: Collaborate with peers to tackle a real-world manufacturing problem using AI solutions. Present your final project as a team.
Module 8
Who Should Enrol?
- Students: Undergraduates and postgraduates with an interest in AI, robotics, and manufacturing technologies. Basic programming knowledge is helpful.
- Ph.D. Scholars / Researchers: Those researching AI, machine learning, or manufacturing systems, looking to apply AI to their work.
- Academicians / Faculty: Professors and lecturers teaching AI, robotics, or engineering, aiming to enhance their expertise and integrate industry trends.
- Industry Professionals: Professionals in manufacturing, AI, and robotics seeking hands-on experience with AI applications in Industry 5.0.
Module 9
Important Dates
Module 10
Registration Ends
02/05/2026
IST 4:30 PM
Module 11
Workshop Dates
02/05/2026 β 02/07/2026
IST 5:30 PM
Module 12
Workshop Outcomes
- Master AI tools like Google Colab and TensorFlow for manufacturing challenges.
- Develop predictive maintenance models to prevent failures.
- Optimize processes with reinforcement learning.
- Implement AI-driven robotics for automation.
- Apply AI for resource optimization and sustainability.
- Collaborate on real-world AI projects, enhancing problem-solving skills.
Module 13
Fee Structure
Module 14
Student
βΉ1999 | $60
Module 15
Ph.D. Scholar / Researcher
βΉ2999 | $70
Module 16
Academician / Faculty
βΉ3999 | $80
Module 17
Industry Professional
βΉ5999 | $100
Module 18
What You’ll Gain
- Live & recorded sessions
- e-Certificate upon completion
- Post-workshop query support
- Hands-on learning experience
Module 19
Join Our Hall of Fame!
Take your research to the next level with NanoSchool.
Module 20
Publication Opportunity
Get published in a prestigious open-access journal.
Module 21
Centre of Excellence
Become part of an elite research community.
Module 22
Networking & Learning
Connect with global researchers and mentors.
Module 23
Global Recognition
Worth βΉ20,000 / $1,000 in academic value.
Module 24
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