AI+ Manufacturing Practitioner™

Master AI-Driven Manufacturing Excellence for Smarter, Safer, and More Efficient Operations

The AI+ Manufacturing Practitioner certification prepares you to apply AI across production, maintenance, quality, supply chain, and plant operations. You will learn to improve efficiency, predict equipment failures, reduce downtime, strengthen quality control, and support faster operational decisions. The certification covers manufacturing data readiness, vision-based inspection, equipment monitoring, process optimization, AI architecture, implementation planning, responsible AI, security, and ROI measurement. You will also gain practical experience using tools such as ChatGPT, Teachable Machine, Looker Studio, Google Sheets, Miro, and draw.io.

Módulos

  • Module 1: AI in Manufacturing - Context and Opportunities :
    1. 1.1 AI Fundamentals in Manufacturing
    2. 1.2 AI Across Plant Operations
    3. 1.3 Human and Business Context of AI Adoption
    4. 1.4 Use-Cases
    5. 1.5 Case Studies
    6. 1.6 Hands-On
  • Module 2: Core AI Applications in Manufacturing:
    1. 2.1 Vision AI in Manufacturing
    2. 2.2 Maintenance and Reliability AI
    3. 2.3 Operational AI in Manufacturing
    4. 2.4 AI in Planning and Automation
    5. 2.5 Use-Cases
    6. 2.6 Case Studies
    7. 2.7 Hands-On Exercise
  • Module 3: Manufacturing Data and Readiness :
    1. 3.1 Types of Manufacturing Data
    2. 3.2 Data Readiness Requirements
    3. 3.3 Common Readiness Challenges
    4. 3.4 Use-Cases
    5. 3.5 Case Studies
    6. 3.6 Hands-On Exercise: Manufacturing KPI Dashboard Creation using Looker Studio
  • Module 4: AI Systems and Architecture in Manufacturing:
    1. 4.1 Deployment Approaches for Industrial AI
    2. 4.2 AI System Structure
    3. 4.3 Integration and Solution Evaluation
    4. 4.4 Use-Cases
    5. 4.5 Case Studies
    6. 4.6 Hands-On Exercise: AI System Architecture Mapping Exercise using Miro or draw.io
  • Module 5: Implementing AI in Manufacturing :
    1. 5.1 Identifying and Prioritizing AI Opportunities
    2. 5.2 Pilot and Proof-of-Concept Design
    3. 5.3 Measuring and Scaling AI Impact
    4. 5.4 Real-World Implementation Constraints
    5. 5.5 Use-Cases
    6. 5.6 Case Studies
    7. 5.7 Hands-On Exercise: AI Pilot and Implementation Roadmap Workshop using Miro
  • Module 6: Responsible AI, Safety, and Security:
    1. 6.1 Responsible AI in Industrial Operations
    2. 6.2 Governance and Data Responsibility
    3. 6.3 Security and Safety Risks
    4. 6.4 Human Oversight and Escalation
    5. 6.5 Use-Cases
    6. 6.6 Case Studies
    7. 6.7 Hands-On Exercise: AI Risk and Governance Checklist Exercise using Google Sheets
  • Module 7: AI Success, Failure, and ROI :
    1. 7.1 AI Project Failures in Manufacturing
    2. 7.2 Success Patterns in AI Adoption
    3. 7.3 ROI Frameworks for Manufacturing AI
    4. 7.4 Industry Comparison
    5. 7.5 Use-Cases
    6. 7.6 Case Studies
    7. 7.7 Hands-On Exercise: AI ROI Estimation and Benefit Tracking
  • Module 8: Future Trends in Manufacturing AI :
    1. 8.1 Emerging AI Directions in Manufacturing
    2. 8.2 Digital Twins and Intelligent Monitoring
    3. 8.3 Generative AI in Manufacturing
    4. 8.4 Future Adoption Outlook
    5. 8.5 Use-Cases
    6. 8.6 Case Studies
    7. 8.7 Hands-On: AI Adoption Roadmap Creation
  • Module 9: Capstone Project:
    1. 9.1 Problem Definition and Scope
    2. 9.2 AI Use-Case Selection and Readiness Review
    3. 9.3 Solution Evaluation and Roadmap Development
    4. 9.4 Business Value and Communication
    5. 9.5 Capstone Tracks

Herramientas de IA

  • Tableau
  • Qlik Sense
  • Lucidchart
  • PTC ThingWorx
  • GE Digital Proficy
  • Rockwell Automation FactoryTalk Analytics
  • Ignition by Inductive Automation
  • C3 AI
  • Uptake
  • Augury
  • Cognex VisionPro
  • UiPath
  • Sight Machine
← Volver a cursos