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    • AI+ Manufacturing Practitioner™

    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.
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    AI+ Manufacturing Practitioner™
    Price: USD $195.00

    At a Glance: Course + Exam Overview

    Category AI Business
    AI Professional
    Program Name AI+ Manufacturing Practitioner™
    Prerequisites
      • Understanding of manufacturing operations
      • Familiarity with AI, machine learning, and automation
      • Ability to interpret operational data, dashboards, metrics, and trends
      • Awareness of MES, SCADA, ERP, sensors, and connected platforms
      • Basic business analysis skills
    Exam Format 90 minutes

    What You'll Learn

    • AI Foundations and Opportunities
      Understand AI fundamentals, plant-level applications, human–AI collaboration, business value, practical use cases, and hands-on manufacturing scenarios.
    • Core Manufacturing AI Applications
      Explore vision-based inspection, predictive maintenance, equipment reliability, operational analytics, production planning, intelligent automation, and practical exercises.
    • Manufacturing Data Readiness
      Learn about manufacturing data types, quality requirements, readiness challenges, real-world use cases, and KPI dashboard creation using Looker Studio.
    • Industrial AI Systems and Architecture
      Compare deployment approaches, understand AI system structures, evaluate integration options, and map industrial AI architectures using Miro or draw.io.
    • AI Implementation and Scaling
      Identify valuable AI opportunities, design pilots, measure impact, address implementation constraints, and create scalable adoption roadmaps.
    • Responsible AI, Safety, and Security
      Apply data governance, cybersecurity, operational safety, human oversight, escalation controls, and AI risk assessment practices.
    • AI Performance and Business Value
      Examine project success and failure factors, apply ROI frameworks, compare industry adoption, and estimate measurable operational benefits.
    • Future Manufacturing Technologies
      Explore digital twins, intelligent monitoring, generative AI, emerging technologies, adoption trends, and phased AI roadmap planning.
    • End-to-End Manufacturing Project
      Define a manufacturing problem, assess readiness, select an AI use case, evaluate solutions, develop a roadmap, and communicate business value.

    Certification Modules

    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

    Finish the course and get certified

    Certificate 1

    Industry Opportunities

    • Manufacturing AI Practitioner
      Manufacturing AI Practitioner
      Applies AI solutions across production, maintenance, quality, and planning.
    • Plant Operations Analyst
      Plant Operations Analyst
      Uses operational data to improve plant efficiency and performance.
    • Production and Process Engineer
      Production and Process Engineer
      Applies AI to optimize workflows, throughput, and process stability.
    • Predictive Maintenance Analyst
      Predictive Maintenance Analyst
      Uses equipment data to forecast failures and reduce downtime.
    • Quality Automation Specialist
      Quality Automation Specialist
      Implements AI-based inspection and defect-detection solutions.
    • Industrial Data Analyst
      Industrial Data Analyst
      Analyzes machine, sensor, quality, and production data for insights.
    • IT/OT Integration Specialist
      IT/OT Integration Specialist
      Connects AI solutions with MES, SCADA, ERP, and plant systems.
    • Smart Manufacturing Consultant
      Smart Manufacturing Consultant
      Advises manufacturers on AI adoption, automation, and implementation.
    • Manufacturing Transformation Lead
      Manufacturing Transformation Lead
      Directs AI initiatives, measures ROI, and scales digital transformation.

    Frequently Asked Questions

    You will learn manufacturing AI, predictive maintenance, computer vision, data readiness, system integration, KPI measurement, and responsible AI.

    The exam includes 50 questions, lasts 90 minutes, and requires a 70% passing score.

    Yes. The course includes hands-on projects, exercises, and manufacturing case studies.

    Tools include Tableau, Qlik Sense, PTC ThingWorx, C3 AI, Augury, Cognex VisionPro, UiPath, and Sight Machine.

    It builds practical skills in predictive maintenance, quality inspection, industrial analytics, automation, system integration, and responsible AI.

    Prerequisites

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    Exam Details

    Duration

    90 minutes

    Format

    50 multiple-choice/multiple-response questions

    Exam Blueprint

    AI in Manufacturing: Context and Opportunities 5%
    Core AI Applications in Manufacturing 11%
    Manufacturing Data and Readiness 12%
    AI Systems and Architecture in Manufacturing 12%
    Implementing AI in Manufacturing 12%
    Responsible AI, Safety, and Security 12%
    AI Success, Failure, and ROI 12%
    Future Trends in Manufacturing AI 12%
    Capstone Project 12%
    Course Price: USD $195.00
    Self-Paced Online
    Purchase Self-Paced Course
    Instructor-Led (Live Virtual/Classroom)