Introduction to CRISP-DM in Manufacturing (Pilot)

Type of course:

Digital learning, Lesson

Language:

Duration:

5 minutes

Proficiency:

Beginner

Target:

Manager, Professionals, Workers

SUMMARY

What makes a data science project truly successful? Is it cutting-edge algorithms or something simpler—a clear and systematic approach?

In this lesson, Introduction to Cross Industry Standard Process for Data Mining (CRISP-DM), you will explore a proven framework that guides data science projects from start to finish. CRISP-DM is an adaptable tool that empowers manufacturing professionals to address real-world challenges with clarity and focus.

Discover how CRISP-DM helps align projects with business goals, ensuring measurable success. From reducing downtime to enhancing product quality, this framework provides the structure to transform raw data into actionable insights.

By the end of this lesson, you will master the six phases of CRISP-DM and understand their direct application to manufacturing, enabling you to lead impactful data science initiatives confidently.

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, learners will be able to define the six phases of CRISP-DM (Cross Industry Standard Process for Data Mining) and their relevance to manufacturing projects.
By the end of this lesson, learners will be able to identify how the framework applies to common manufacturing challenges and data-driven solutions.
By the end of this lesson, learners will be able to explain how the framework allows for revisiting and refining phases to address evolving project needs and ensure continuous improvement.