CRISP-DM Methodology

Type of course:

Digital learning, Lesson

Language:

Duration:

10 minutes

Workload:

2 hours

Proficiency:

Beginner

Target:

Professionals

This nugget dives into the world of data-driven decision-making using the CRISP-DM methodology.

The student will discover how it is constructed into six unique stages, which turns it into one of the most adopted methodologies to develop real-world data mining and machine learning projects.

Formative assessment is presented in the end to support the student’s comprehension of the materials.

Learning outcomes

Students will describe the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology and its significance as a comprehensive framework for guiding data-driven projects from start to finish.
Students will explain the six stages of CRISP-DM and how each stage contributes to transforming data into actionable insights.
Students will recognize how the CRISP-DM methodology is applied to solve a real-world manufacturing problem.