Skills you will learn

  • Human-AI Collaboration
  • Edge AI vs. Cloud AI
  • Manufacturing Data (PLC, SCADA, MES, ERP)
  • Structured and Unstructured Data
  • AI-Powered Quality Inspection
  • Predictive Maintenance
  • Robotics
  • AI Prompt Engineering
  • AI-Based Troubleshooting
  • Responsible AI

Who should learn

  • Manufacturing Professionals
  • Operations Managers
  • Supply Chain Professionals
  • Production Supervisors
  • Engineering Students
  • Business Analysts
  • Beginners
  • Students

What you will learn

  • Free AI in Manufacturing Course with Certificate 2026

    • Lesson 01: Course Introduction

      06:34
      • 1.01 Introduction to AI in Manufacturing
        02:05
      • 1.02 Kickstarting with AI in Manufacturing
        04:29
    • Lesson 02: Fundamentals of AI in Manufacturing

      01:49:22
      • 2.01 Learning Objectives
        02:22
      • 2.02 Artificial Intelligence AI
        02:15
      • 2.03 AI Machine Learning and Deep Learning
        02:19
      • 2.04 Evolution of AI
        05:21
      • 2.05 Types of AI
        03:33
      • 2.06 Key Components of AI
        05:37
      • 2.07 AI in Everyday Life Real World Applications
        03:35
      • 2.08 AI Benefits and Challenges
        06:15
      • 2.09 Why Is AI Powerful
        03:14
      • 2.10 What Is Machine Learning
        03:40
      • 2.11 What Is Deep Learning
        03:30
      • 2.12 Three Ways AI Learns
        02:45
      • 2.13 What Is Generative AI
        03:10
      • 2.14 Traditional AI vs Generative AI
        01:56
      • 2.15 Introduction to AI in Manufacturing
        02:53
      • 2.16 How AI Learns in Manufacturing
        02:58
      • 2.17 Computer Vision and Its Applications in Manufacturing
        03:32
      • 2.18 Applying AI Across Manufacturing Operations
        02:44
      • 2.19 Understanding AI Agents and Their Capabilities
        05:54
      • 2.20 Comparing Traditional Automation and AI Agents
        03:44
      • 2.21 Case Study Reducing Production Bottlenecks with AI
        05:50
      • 2.22 Case Study AI Assisted Quality Inspection on the Production Line
        03:48
      • 2.23 Demo Identifying AI-Enabled Tasks in a Manufacturing Scenario Using ChatGpt
        12:30
      • 2.24 Demo Using ChatGPT to Evaluate and Act on AI Recommendations
        13:43
      • 2.25 Key Takeaways
        02:14
    • Lesson 03: Evolution of AI and Industry Standards

      59:18
      • 3.01 Evolution of AI and Industry Standards Learning Objectives
        01:52
      • 3.02 The Evolution of Manufacturing
        02:43
      • 3.03 Human and AI Collaboration in Manufacturing
        02:17
      • 3.04 Building Blocks of Smart Manufacturing
        02:38
      • 3.05 How Data Is Transformed into Decisions
        02:34
      • 3.06 From Factory Data Flow to Better Decisions
        03:48
      • 3.07 AI Powered Factory Management Systems
        02:14
      • 3.08 Traditional vs AI Enhanced Factory Management
        02:43
      • 3.09 Introduction to the ISO IEC 42001 Framework
        01:25
      • 3.10 The Role of ISO IEC 42001 in AI Governance
        02:16
      • 3.11 How Manufacturing Intelligence Has Evolved
        02:00
      • 3.12 How the Role of AI Has Expanded
        01:57
      • 3.13 Edge AI vs Cloud AI
        01:22
      • 3.14 What Runs on the Machine and What Runs in the Cloud
        02:40
      • 3.15 Combining Edge AI and Cloud AI in Manufacturing
        02:04
      • 3.16 Case Study Connecting Shop Floor to Boardroom with AI
        05:40
      • 3.17 Case Study Predicting Maintenance Needs Before Failure
        05:46
      • 3.18 Demo Implementing AI Human Collaboration Across Manufacturing Activities Using Claude
        11:01
      • 3.19 Evolution of AI and Industry Standards Key Takeaways
        02:18
    • Lesson 04: Manufacturing Data for AI

      51:10
      • 4.01 Manufacturing Data for AI Learning Objectives
        02:16
      • 4.02 Data Sources for AI in Manufacturing
        02:50
      • 4.03 Understanding Manufacturing Data
        01:59
      • 4.04 Data Format Structured Data vs Unstructured Data
        01:51
      • 4.05 Operational Context OT and IT Data
        01:57
      • 4.06 Source Systems
        01:44
      • 4.07 PLC Programmable Logic Controller Data in Manufacturing
        02:20
      • 4.08 SCADA Supervisory Control and Data Acquisition Data in Manufacturing
        02:49
      • 4.09 MES Manufacturing Execution System Data in Manufacturing
        02:31
      • 4.10 ERP Enterprise Resource Planning Data in Manufacturing
        02:06
      • 4.11 Unlocking Historical Data
        03:05
      • 4.12 Connecting Factory Systems Through Data
        02:38
      • 4.13 Building Reliable Manufacturing Data
        02:48
      • 4.14 Data Labeling
        01:34
      • 4.15 Case Study Data Efficient AI for Manufacturing Decisions
        05:30
      • 4.16 Demo Tracing the Data Journey from Sensor to AI Insight Using Claude
        11:14
      • 4.17 Manufacturing Data for AI Key Takeaways
        01:58
    • Lesson 05: AI Applications in Manufacturing Operations

      01:14:20
      • 5.01 AI Applications in Manufacturing Operations Learning Objectives
        01:28
      • 5.02 Automating Quality Inspection with AI
        01:47
      • 5.03 Applying AI Based Defect Detection Across Industries
        03:45
      • 5.04 Moving from Defect Detection to Defect Prevention
        01:43
      • 5.05 Building Autonomous Quality Systems
        01:55
      • 5.06 Understanding and Comparing Maintenance Approaches
        03:59
      • 5.07 Case Study AI Vision for Process Visibility and Downtime Reduction
        04:11
      • 5.08 Predictive Maintenance Workflow
        02:14
      • 5.09 Case Study AI for Predictive Maintenance and Energy Optimization
        04:24
      • 5.10 Demo Responding to an AI Generated Machine Alert Using ChatGPT
        11:12
      • 5.11 Monitoring Workplace Safety with AI
        02:50
      • 5.12 Traditional Monitoring vs AI Assisted Safety
        01:54
      • 5.13 Case Study AI Based Safety Monitoring in Manufacturing
        04:59
      • 5.14 AI Assisted Inventory Planning in Supply Chain Management
        04:02
      • 5.15 Digital Twins and Their Benefits in Manufacturing
        03:18
      • 5.16 Case Study Digital Twin for Production Optimization
        04:35
      • 5.17 How AI Powered Robots Assist in Manufacturing
        02:06
      • 5.18 Demo Matching AI Powered Robotic Solutions to Manufacturing Challenges Using ChatGPT
        11:36
      • 5.19 AI Applications in Manufacturing Operations Key Takeaways
        02:22
    • Lesson 06: Using Generative AI Effectively in Manufacturing

      01:13:47
      • 6.01 Using Generative AI Effectively in Manufacturing Learning Objectives
        00:56
      • 6.02 Using Generative AI Effectively in Manufacturing
        02:41
      • 6.03 Building Effective AI Prompts
        02:32
      • 6.04 Avoiding Common AI Mistakes and Hallucinations​
        03:09
      • 6.05 Using Multimodal AI​
        01:28
      • 6.06 Demo Analyzing a Manufacturing Problem from a Photograph Using ChatGPT
        14:08
      • 6.07 GenAI Applications Across Manufacturing Workflows​
        00:37
      • 6.08 Creating Clear Documents with AI​
        01:21
      • 6.09 Demo Transforming a Rough Draft into a Clear Work Instruction Using Gemini
        06:52
      • 6.10 Demo Creating Shift Summaries with Gemini
        06:01
      • 6.11 Troubleshooting with AI
        01:27
      • 6.12 Demo Troubleshooting a Machine Alert Using Gemini
        12:21
      • 6.13 Creating Visual Aids with AI​
        01:11
      • 6.14 Demo Generating a Process Communication Poster Using Gemini
        05:55
      • 6.15 Getting Insights from Data Using AI​
        01:41
      • 6.16 Demo Asking a Data Question and Getting an Instant Answer Using ChatGPT
        05:40
      • 6.17 Case Study AI Assisted Engineering Documentation​
        02:11
      • 6.18 Case Study Multilingual Safety Training Across Industrial Operations​
        02:13
      • 6.19 Using Generative AI Effectively in Manufacturing Key Takeaways
        01:23
    • Lesson 07: Implementing Generative AI Across Manufacturing Operations

      45:16
      • 7.01 Implementing Generative AI Across Manufacturing Operations Learning Objectives
        01:09
      • 7.02 Using GenAI to Identify and Resolve Maintenance Issues
        02:47
      • 7.03 Case Study GenAI for Maintenance Recommendations
        03:50
      • 7.04 Quality Reporting with GenAI
        01:20
      • 7.05 Case Study AI Assisted Quality Inspection
        04:05
      • 7.06 GenAI Support for Scheduling and Planning
        01:41
      • 7.07 AI Recommendations vs Autonomous Actions
        01:16
      • 7.08 Case Study AI Powered Production Scheduling
        04:04
      • 7.09 How GenAI Improves Multilingual Work Instructions
        01:55
      • 7.10 Case Study AI Powered Multilingual Training Videos
        03:38
      • 7.11 GenAI for Demand Forecasting
        01:21
      • 7.12 Measuring the Value of AI
        02:29
      • 7.13 Case Study AI Powered Customized Manufacturing at Scale
        04:25
      • 7.14 Demo Supporting an Inventory or Scheduling Decision Using Claude
        09:30
      • 7.15 Implementing Generative AI Across Manufacturing Operations Key Takeaways
        01:46
    • Lesson 08: AI Ethics, Privacy, and Safety

      56:36
      • 8.01 AI Ethics Privacy and Safety Learning Objectives
        01:27
      • 8.02 Responsible AI Practices at Work
        02:07
      • 8.03 Sharing Information with AI Responsibly
        02:57
      • 8.04 AI Bias in Data and System Design
        02:32
      • 8.05 Case Study Evaluating AI Bias in Candidate Shortlisting
        05:03
      • 8.06 Understanding AI Outputs
        01:04
      • 8.07 Demo Evaluating an AI Recommendation Using Claude
        08:47
      • 8.08 Establishing AI Governance Practices
        02:28
      • 8.09 AI Security Risks
        02:01
      • 8.10 Case Study Building a Secure Connected Factory with AI
        04:44
      • 8.11 Deciding How to Act on AI Outputs
        03:11
      • 8.12 Assessing AI Recommendations Before Action
        02:58
      • 8.13 Demo Evaluating AI Recommendations Responsibly Using Claude
        08:16
      • 8.14 Demo Rewriting a Biased or Poorly Framed Prompt Using Claude
        07:29
      • 8.15 AI Ethics Privacy and Safety Key Takeaways
        01:32
    • Lesson 09: The Future of AI in Manufacturing

      41:15
      • 9.01 The Future of AI in Manufacturing Learning Objectives
        01:24
      • 9.02 How AI is Changing Manufacturing Roles
        01:38
      • 9.03 What AI Cannot Replace
        01:12
      • 9.04 Agentic AI Moving from Recommendations to Actions
        01:57
      • 9.05 Using AI to Find Energy and Waste Opportunities
        01:45
      • 9.06 Case Study AI for Energy Optimization
        04:17
      • 9.07 AI Adoption Challenges and Considerations
        01:39
      • 9.08 Case Study Building a Secure Connected Factory with AI
        04:26
      • 9.09 Case Study AI Powered Collaborative Robots in Manufacturing
        03:31
      • 9.10 Introduction to Physical AI
        01:34
      • 9.11 Industrial Foundation Models
        01:48
      • 9.12 AI Adoption Across Manufacturing Roles
        01:24
      • 9.13 Core Skills for AI Adoption in Manufacturing
        01:54
      • 9.14 Demo Mapping Your AI Learning Journey Using Claude
        11:20
      • 9.15 The Future of AI in Manufacturing Key Takeaways
        01:26
About the Course

Factories produce huge amounts of data every day. AI can turn that data into better decisions, but only if you know what it can do, what it needs, and where people still matter.

In this course, you'll learn the basics of AI, machine learning, deep learning, and generative AI. You'll see how data flows from machines and systems like PLC, SCADA, MES, and ERP into AI tools. You'll look at AI in quality inspection, predictive maintenance, workplace safety, inventory planning, digital twins, and robotics.Read More

For Business

Get your team an enterprise platform to build
an AI-ready workforce at scale.

People Frame

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

FAQs

  • What is AI in manufacturing?

    It's using AI to help with tasks like inspecting products, predicting machine problems, planning production, and keeping workers safe. It helps teams make faster and better decisions using factory data.

  • Do I need a technical background to take this course?

    No. The course starts from the basics and explains each idea in plain language. No coding is needed.

  • What's the difference between AI, machine learning, and deep learning?

    Technology

    Definition

    Example

    Artificial Intelligence (AI)

    Machines performing tasks that typically require human intelligence.

    AI-powered robots

    Machine Learning (ML)

    A subset of AI that learns patterns from data to make predictions or decisions.

    Predictive maintenance

    Deep Learning (DL)

    A subset of ML that uses multi-layered neural networks to learn complex patterns.

    AI-based defect detection

  • What is generative AI, and how is it used in manufacturing?

    Generative AI creates new content such as text, images, and summaries. In manufacturing, it can help write work instructions, create shift summaries, and troubleshoot machine alerts.

  • What kind of manufacturing data does the course cover?

    You'll learn about data from PLC, SCADA, MES, and ERP systems. You'll also see the difference between structured and unstructured data, and between OT and IT data.

  • What is predictive maintenance?

    It's using AI to spot signs of trouble in a machine before it breaks down. This helps teams plan repairs early and avoid unplanned downtime.

  • What is a digital twin?

    It's a virtual copy of a machine, process, or factory that updates with real data. Teams use it to test changes and improve production without risking the real line.

  • What is the difference between edge AI and cloud AI?

    Edge AI runs on or near the machine, so it can respond quickly. Cloud AI runs on remote servers and can handle larger tasks. The course shows how the two can work together.

  • What is agentic AI?

    It's AI that can take actions on its own, not just make suggestions. The course looks at how this may change manufacturing work and why human oversight still matters.

  • Which AI tools are used in the course?

    You'll work with ChatGPT, Claude, and Gemini in the demos. They're used for tasks like analyzing a photo, writing work instructions, and troubleshooting alerts.

  • Will AI replace manufacturing jobs?

    The course looks at how AI is changing roles and what it can't replace. It shows how people and AI can work together, and which skills matter most.

  • How does the course cover ethics and safety?

    You'll learn how to share information with AI responsibly, spot bias in data, and handle AI security risks. You'll also practice checking AI recommendations before acting on them.

  • What demos and case studies are included in the course?

    There are 17 demos and 21 case studies. They cover topics like quality inspection, predictive maintenance, safety monitoring, digital twins, multilingual training, and energy savings.

  • How long will the course take?

    The course has nine lessons and about eight hours of video. You can go at your own pace.

  • Is this course really , and will I get a certificate?

    Yes. You can watch all the lessons and earn your certificate for free. Once you finish, you can share it on LinkedIn or add it to your resume.

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  • Career Impact Results vary based on experience and numerous factors.