About This Course
This comprehensive 2-day training program is designed to equip professionals in manufacturing and production with the knowledge, skills, and tools to leverage Artificial Intelligence (AI) effectively. Participants will explore foundational concepts of AI, including Generative AI, Agentic AI, and their applications in the manufacturing sector. The course blends theoretical insights with practical, hands-on workshops, enabling attendees to design and implement AI-driven solutions for real-world manufacturing challenges.
Learning Objectives
By the end of this course, participants will:
- Understand AI concepts, including Generative and Agentic AI, and their applications in manufacturing.
- Identify and apply AI use cases like predictive maintenance, quality control, and generative design.
- Prepare and manage data effectively for AI applications using IoT and real-time data.
- Develop and implement AI project plans to solve specific manufacturing challenges.
- Integrate responsible AI practices, ensuring fairness and transparency.
- Collaborate in teams to design and pitch AI-driven solutions tailored to manufacturing needs.
Prerequisites
Basic understanding of manufacturing processes and a keen interest in AI applications. No prior AI knowledge is required
Target Audience
This course is tailored for professionals in the manufacturing and production industries, including operations managers, engineers, data analysts, and decision-makers looking to leverage AI for efficiency and innovation.
Training Outline
Day 1: AI Fundamentals in Manufacturing
- What is AI? Overview of AI and its capabilities in manufacturing.
- Generative AI Vs Non-Generative AI Understanding key differences and applications.
- How Does AI Work? Basics of machine learning and data processing.
- How Would AI Impact Jobs? Transformation of roles in the workplace.
- How Would AI Change the Way We Work? AI integration in workflows.
- AI Use Cases in Industries Predictive maintenance, quality control, and more.
- Agentic AI in Manufacturing Autonomous AI-driven decision-making applications.
- Data and Features Understanding data in AI models.
- Machine Learning Algorithms Overview of supervised and unsupervised learning.
- AI Model Training & Deployment Practical insights into AI implementation.
- Responsible AI & Ethics Fairness, accountability, and transparency in AI.
- Live Demonstration AI-Powered Tomato Sorter in action.
Day 2: AI Implementation and Project Design
- Introduction to AI in Manufacturing Industry 4.0 and latest AI trends.
- Key AI Applications in Manufacturing Predictive maintenance, generative design, and supply chain optimization.
- Data Preparation for AI Leveraging IoT and real-time data.
- Introduction to AI Thinking Developing problem-solving approaches with AI.
- How to Plan an AI Project? Case study of an AI-powered Tomato Sorter.
- Hands-On Workshop Designing AI solutions for manufacturing challenges.
- AI Project Idea Pitching Group presentations and feedback.
- Wrap-Up and Q&A Summarizing key takeaways and addressing questions.