Course Test - Quality Control (Pilot)

Type of course:

Digital learning, Lesson

Language:

Duration:

20 minutes

Workload:

2 hours

Proficiency:

Intermediate

Target:

Manager, Professionals, Workers

SUMMARY

Welcome to the assessment for the “Data-Driven Quality Control” course!

Good luck, and let’s see how well you grasp the essential principles of data-driven quality control!

About The Author

Dilek Dustegor is a Professor of Computing Science at the University of Groningen in the Netherlands. She is interested in bridging the gaps between research, development and implementation using AI and automation. She is pursuing research about modeling, design and analysis of large scale / networked systems using IoT and ML techniques, with a special interest in smart city applications. She is a seasoned educator, and loves using the newest educational technologies for an enhanced learning experience.

Learning outcomes

By the end of this lesson, students will be able to explain relevant data science techniques and tools to process and analyze manufacturing data in solving a quality control problem for the detection of defects, reducing errors, and ensuring higher product quality.
By the end of this lesson, students will be able to abstract the quality control problem and formulate it as a set of appropriate data science and machine learning problems.
By the end of this lesson, students will be able to apply relevant data science techniques and tools to process and analyze manufacturing data in solving a quality control problem for the detection of defects, reducing errors, and ensuring higher product quality.