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Data Science Foundations: Data Mining Course

Data Science Foundations: Data Mining Course
from 4 to 360h flexible workload
valid certificate in your country

What will I learn?

Master the essentials of data mining with a focused, hands-on course tailored to real operational datasets. Learn data ingestion, validation, and cleaning, then explore EDA, visualization, association rules, clustering, and classification. Build reliable features, apply robust evaluation, and understand deployment basics so you can turn complex data into clear, actionable safety and performance insights fast.

Elevify advantages

Develop skills

  • Clean mining data pipelines: validate schemas, fix outliers, and impute gaps fast.
  • Discover risk patterns: apply association rules to uncover hidden safety drivers.
  • Segment mine operations: use clustering to flag high-risk, high-impact sites.
  • Build safety classifiers: train, tune, and explain models for incident prediction.
  • Engineer mining features: create robust time-based, spatial, and operational signals.

Suggested summary

Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.
Workload: between 4 and 360 hours

What our students say

Your classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the extra videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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