Free AI in Manufacturing Course with Certificate 2026

2.01 Learning Objectives

2.02 Artificial Intelligence AI

2.03 AI Machine Learning and Deep Learning

2.04 Evolution of AI

2.05 Types of AI

2.06 Key Components of AI

2.07 AI in Everyday Life Real World Applications

2.08 AI Benefits and Challenges

2.09 Why Is AI Powerful

2.10 What Is Machine Learning

2.11 What Is Deep Learning

2.12 Three Ways AI Learns

2.13 What Is Generative AI

2.14 Traditional AI vs Generative AI

2.15 Introduction to AI in Manufacturing

2.16 How AI Learns in Manufacturing

2.17 Computer Vision and Its Applications in Manufacturing

2.18 Applying AI Across Manufacturing Operations

2.19 Understanding AI Agents and Their Capabilities

2.20 Comparing Traditional Automation and AI Agents

2.21 Case Study Reducing Production Bottlenecks with AI

2.22 Case Study AI Assisted Quality Inspection on the Production Line

2.23 Demo Identifying AI-Enabled Tasks in a Manufacturing Scenario Using ChatGpt

2.24 Demo Using ChatGPT to Evaluate and Act on AI Recommendations

2.25 Key Takeaways

3.01 Evolution of AI and Industry Standards Learning Objectives

3.02 The Evolution of Manufacturing

3.03 Human and AI Collaboration in Manufacturing

3.04 Building Blocks of Smart Manufacturing

3.05 How Data Is Transformed into Decisions

3.06 From Factory Data Flow to Better Decisions

3.07 AI Powered Factory Management Systems

3.08 Traditional vs AI Enhanced Factory Management

3.09 Introduction to the ISO IEC 42001 Framework

3.10 The Role of ISO IEC 42001 in AI Governance

3.11 How Manufacturing Intelligence Has Evolved

3.12 How the Role of AI Has Expanded

3.13 Edge AI vs Cloud AI

3.14 What Runs on the Machine and What Runs in the Cloud

3.15 Combining Edge AI and Cloud AI in Manufacturing

3.16 Case Study Connecting Shop Floor to Boardroom with AI

3.17 Case Study Predicting Maintenance Needs Before Failure

3.18 Demo Implementing AI Human Collaboration Across Manufacturing Activities Using Claude

3.19 Evolution of AI and Industry Standards Key Takeaways

4.01 Manufacturing Data for AI Learning Objectives

4.02 Data Sources for AI in Manufacturing

4.03 Understanding Manufacturing Data

4.04 Data Format Structured Data vs Unstructured Data

4.05 Operational Context OT and IT Data

4.06 Source Systems

4.07 PLC Programmable Logic Controller Data in Manufacturing

4.08 SCADA Supervisory Control and Data Acquisition Data in Manufacturing

4.09 MES Manufacturing Execution System Data in Manufacturing

4.10 ERP Enterprise Resource Planning Data in Manufacturing

4.11 Unlocking Historical Data

4.12 Connecting Factory Systems Through Data

4.13 Building Reliable Manufacturing Data

4.14 Data Labeling

4.15 Case Study Data Efficient AI for Manufacturing Decisions

4.16 Demo Tracing the Data Journey from Sensor to AI Insight Using Claude

4.17 Manufacturing Data for AI Key Takeaways

5.01 AI Applications in Manufacturing Operations Learning Objectives

5.02 Automating Quality Inspection with AI

5.03 Applying AI Based Defect Detection Across Industries

5.04 Moving from Defect Detection to Defect Prevention

5.05 Building Autonomous Quality Systems

5.06 Understanding and Comparing Maintenance Approaches

5.07 Case Study AI Vision for Process Visibility and Downtime Reduction

5.08 Predictive Maintenance Workflow

5.09 Case Study AI for Predictive Maintenance and Energy Optimization

5.10 Demo Responding to an AI Generated Machine Alert Using ChatGPT

5.11 Monitoring Workplace Safety with AI

5.12 Traditional Monitoring vs AI Assisted Safety

5.13 Case Study AI Based Safety Monitoring in Manufacturing

5.14 AI Assisted Inventory Planning in Supply Chain Management

5.15 Digital Twins and Their Benefits in Manufacturing

5.16 Case Study Digital Twin for Production Optimization

5.17 How AI Powered Robots Assist in Manufacturing

5.18 Demo Matching AI Powered Robotic Solutions to Manufacturing Challenges Using ChatGPT

5.19 AI Applications in Manufacturing Operations Key Takeaways

6.01 Using Generative AI Effectively in Manufacturing Learning Objectives

6.02 Using Generative AI Effectively in Manufacturing

6.03 Building Effective AI Prompts

6.04 Avoiding Common AI Mistakes and Hallucinations​

6.05 Using Multimodal AI​

6.06 Demo Analyzing a Manufacturing Problem from a Photograph Using ChatGPT

6.07 GenAI Applications Across Manufacturing Workflows​

6.08 Creating Clear Documents with AI​

6.09 Demo Transforming a Rough Draft into a Clear Work Instruction Using Gemini

6.10 Demo Creating Shift Summaries with Gemini

6.11 Troubleshooting with AI

6.12 Demo Troubleshooting a Machine Alert Using Gemini

6.13 Creating Visual Aids with AI​

6.14 Demo Generating a Process Communication Poster Using Gemini

6.15 Getting Insights from Data Using AI​

6.16 Demo Asking a Data Question and Getting an Instant Answer Using ChatGPT

6.17 Case Study AI Assisted Engineering Documentation​

6.18 Case Study Multilingual Safety Training Across Industrial Operations​

6.19 Using Generative AI Effectively in Manufacturing Key Takeaways

7.01 Implementing Generative AI Across Manufacturing Operations Learning Objectives

7.02 Using GenAI to Identify and Resolve Maintenance Issues

7.03 Case Study GenAI for Maintenance Recommendations

7.04 Quality Reporting with GenAI

7.05 Case Study AI Assisted Quality Inspection

7.06 GenAI Support for Scheduling and Planning

7.07 AI Recommendations vs Autonomous Actions

7.08 Case Study AI Powered Production Scheduling

7.09 How GenAI Improves Multilingual Work Instructions

7.10 Case Study AI Powered Multilingual Training Videos

7.11 GenAI for Demand Forecasting

7.12 Measuring the Value of AI

7.13 Case Study AI Powered Customized Manufacturing at Scale

7.14 Demo Supporting an Inventory or Scheduling Decision Using Claude

7.15 Implementing Generative AI Across Manufacturing Operations Key Takeaways

8.01 AI Ethics Privacy and Safety Learning Objectives

8.02 Responsible AI Practices at Work

8.03 Sharing Information with AI Responsibly

8.04 AI Bias in Data and System Design

8.05 Case Study Evaluating AI Bias in Candidate Shortlisting

8.06 Understanding AI Outputs

8.07 Demo Evaluating an AI Recommendation Using Claude

8.08 Establishing AI Governance Practices

8.09 AI Security Risks

8.10 Case Study Building a Secure Connected Factory with AI

8.11 Deciding How to Act on AI Outputs

8.12 Assessing AI Recommendations Before Action

8.13 Demo Evaluating AI Recommendations Responsibly Using Claude

8.14 Demo Rewriting a Biased or Poorly Framed Prompt Using Claude

8.15 AI Ethics Privacy and Safety Key Takeaways

9.01 The Future of AI in Manufacturing Learning Objectives

9.02 How AI is Changing Manufacturing Roles

9.03 What AI Cannot Replace

9.04 Agentic AI Moving from Recommendations to Actions

9.05 Using AI to Find Energy and Waste Opportunities

9.06 Case Study AI for Energy Optimization

9.07 AI Adoption Challenges and Considerations

9.08 Case Study Building a Secure Connected Factory with AI

9.09 Case Study AI Powered Collaborative Robots in Manufacturing

9.10 Introduction to Physical AI

9.11 Industrial Foundation Models

9.12 AI Adoption Across Manufacturing Roles

9.13 Core Skills for AI Adoption in Manufacturing

9.14 Demo Mapping Your AI Learning Journey Using Claude

9.15 The Future of AI in Manufacturing Key Takeaways