Yellow Belt Training: Enhance Your Strategic Decision Making Around the Use of Key AI Technologies.
What you'll learn: Requirements: Description: Who this course is for:
How AI tools are applied to solve complex problems
Understand the challenges posed by manufacturing big data.
Learn to develop Cyber-Physical Systems to solve engineering intractable problems
How to drive innovation in manufacturing
Limitations of quality control systems
Advantages of learning Quality 4.0
No programming or machine learning background is required
In the manufacturing industry, the transformative potential of artificial intelligence (AI) is widely acknowledged. The current era witnesses the pervasive industrialization of AI, with a particular emphasis on its role in enhancing quality control, a focal point across industries.This course centers around pivotal AI technologies, notably machine learning and deep learning, aiming to empower managers in crafting a visionary outlook for Quality 4.0 and assisting engineers in devising and executing intelligent quality systems. Rooted in theory, empirical evidence, a diverse array of techniques, and the author's extensive experience studying complex manufacturing systems, the course content is meticulously curated.Our deliberate approach ensures that mathematical and coding complexities remain accessible to engineers, enabling a sharper focus on practical problem-solving through AI. Engage in an immersive exploration encompassing key technology introductions, profound manufacturing insights, compelling case examples, and the opportunity to undertake a business-oriented project.Embark on a journey that illuminates the essence of central Quality 4.0 today and its potential to catalyze innovation to solve a whole new range of engineering intractable problems. The course encompasses a broad spectrum of knowledge areas, including programming, smart manufacturing, quality control, statistics, optimization, machine learning, and a novel 5-step problem-solving strategy tailored for Quality 4.0 deployment.
Manufacturing technicians, engineers, managers and directors
Professionals interested in smart manufacturing
Professionals interested in learning how machine learning can be applied to drive innovation.
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