AI+ Manufacturing Practitioner

Hours: 8 / Access Length: 12 Months / Delivery: Online, Self-Paced
Online Hours: 8
Retail Price: $195.00

Course Overview:

The AI+ Manufacturing Practitioner certification equips professionals to understand and apply artificial intelligence across production, maintenance, quality, supply chain, planning, and automation. Learners explore industrial data, vision AI, predictive maintenance, system architecture, implementation planning, responsible AI, cybersecurity, safety, return on investment, and emerging technologies. The program emphasizes practical decision-making through manufacturing use-cases, industry case studies, guided exercises, and a capstone project. Participants learn to assess AI opportunities, evaluate data and system readiness, design pilots, measure operational value, manage implementation risks, and develop phased roadmaps for scalable, responsible AI adoption in manufacturing environments.

Recommended Prerequisites:

• Manufacturing Operations Awareness: Familiarity with production, maintenance, quality, and supply chain processes.
• Fundamental AI Knowledge: Understanding basic AI and machine learning concepts.
• Data Literacy: Ability to interpret operational data, KPIs, and trends.
• Digital Systems Familiarity: Exposure to MES, SCADA, ERP, sensors, or industrial platforms.
• Continuous Improvement Mindset: Interest in solving operational problems through data and technology

Course Outline:

Module 1: AI in Manufacturing - Context and Opportunities

• 1.1 AI Fundamentals in Manufacturing
• 1.2 AI Across Plant Operations
• 1.3 Human and Business Context of AI Adoption
• 1.4 Use-Cases
• 1.5 Case Studies
• 1.6 Hands-On

Module 2: Core AI Applications in Manufacturing

• 2.1 Vision AI in Manufacturing
• 2.2 Maintenance and Reliability AI
• 2.3 Operational AI in Manufacturing
• 2.4 AI in Planning and Automation
• 2.5 Use-Cases
• 2.6 Case Studies
• 2.7 Hands-On Exercise

Module 3: Manufacturing Data and Readiness

• 3.1 Types of Manufacturing Data
• 3.2 Data Readiness Requirements
• 3.3 Common Readiness Challenges
• 3.4 Use-Cases
• 3.5 Case Studies
• 3.6 Hands-On Exercise: Manufacturing KPI Dashboard Creation using Looker Studio

Module 4: AI Systems and Architecture in Manufacturing

• 4.1 Deployment Approaches for Industrial AI
• 4.2 AI System Structure
• 4.3 Integration and Solution Evaluation
• 4.4 Use-Cases
• 4.5 Case Studies
• 4.6 Hands-On Exercise: AI System Architecture Mapping Exercise using Miro or draw.io

Module 5: Implementing AI in Manufacturing

• 5.1 Identifying and Prioritizing AI Opportunities
• 5.2 Pilot and Proof-of-Concept Design
• 5.3 Measuring and Scaling AI Impact
• 5.4 Real-World Implementation Constraints
• 5.5 Use-Cases
• 5.6 Case Studies
• 5.7 Hands-On Exercise: AI Pilot and Implementation Roadmap Workshop using Miro

Module 6: Responsible AI, Safety, and Security

• 6.1 Responsible AI in Industrial Operations
• 6.2 Governance and Data Responsibility
• 6.3 Security and Safety Risks
• 6.4 Human Oversight and Escalation
• 6.5 Use-Cases
• 6.6 Case Studies
• 6.7 Hands-On Exercise: AI Risk and Governance Checklist Exercise using Google Sheets

Module 7: AI Success, Failure, and ROI

• 7.1 AI Project Failures in Manufacturing
• 7.2 Success Patterns in AI Adoption
• 7.3 ROI Frameworks for Manufacturing AI
• 7.4 Industry Comparison
• 7.5 Use-Cases
• 7.6 Case Studies
• 7.7 Hands-On Exercise: AI ROI Estimation and Benefit Tracking

Module 8: Future Trends in Manufacturing AI

• 8.1 Emerging AI Directions in Manufacturing
• 8.2 Digital Twins and Intelligent Monitoring
• 8.3 Generative AI in Manufacturing
• 8.4 Future Adoption Outlook
• 8.5 Use-Cases
• 8.6 Case Studies
• 8.7 Hands-On: AI Adoption Roadmap Creation

Module 9: Capstone Project

• 9.1 Problem Definition and Scope
• 9.2 AI Use-Case Selection and Readiness Review
• 9.3 Solution Evaluation and Roadmap Development
• 9.4 Business Value and Communication
• 9.5 Capstone Tracks

All necessary course materials are included.

System Requirements:

Internet Connectivity Requirements:

• Cable, Fiber, DSL, or LEO Satellite (i.e. Starlink) internet with speeds of at least 10mb/sec download and 5mb/sec upload are recommended for the best experience.

NOTE: While cellular hotspots may allow access to our courses, users may experience connectivity issues by trying to access our learning management system.  This is due to the potential high download and upload latency of cellular connections.   Therefore, it is not recommended that students use a cellular hotspot as their primary way of accessing their courses.

Hardware Requirements:

• CPU: 1 GHz or higher
• RAM: 4 GB or higher
• Resolution: 1280 x 720 or higher.  1920x1080 resolution is recommended for the best experience.
• Speakers / Headphones
• Microphone for Webinar or Live Online sessions.

Operating System Requirements:

• Windows 7 or higher.
• Mac OSX 10 or higher.
• Latest Chrome OS
• Latest Linux Distributions
  

NOTE: While we understand that our courses can be viewed on Android and iPhone devices, we do not recommend the use of these devices for our courses. The size of these devices do not provide a good learning environment for students taking online or live online based courses.

Web Browser Requirements:

• Latest Google Chrome is recommended for the best experience.
• Latest Mozilla FireFox
• Latest Microsoft Edge
• Latest Apple Safari

Basic Software Requirements (These are recommendations of software to use):

• Office suite software (Microsoft Office, OpenOffice, or LibreOffice)
• PDF reader program (Adobe Reader, FoxIt)
• Courses may require other software that is described in the above course outline.