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KNIME Data Analytics Course

5/5
KNIME Data Analytics Course
5.0 in the evaluation
from 4 to 360h flexible workload
valid certificate in your country

What will I learn?

The KNIME Data Analytics Course equips you with hands-on skills to clean, prepare, and analyse data effectively. You will learn data ingestion, preprocessing, aggregation, feature engineering, and visualisation using essential KNIME nodes and best practices. Develop clear, reproducible workflows, validate calculations, and produce dashboard-ready outputs and explanations that address real business questions confidently.

Elevify advantages

Develop skills

  • Clean BI data in KNIME: filters, missing values, outliers fixed quickly.
  • Build reliable KNIME workflows: versioned, documented, and reproducible.
  • Aggregate and rank KPIs in KNIME: revenue, AOV, discounts by key dimensions.
  • Engineer BI features in KNIME: date fields, revenue formulas, smart flags.
  • Create KNIME visuals and exports: dashboard-ready charts, tables, and files.

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 lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to change platforms... I thank you for everything you do, I've already recommended you to other people...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.
André Felipe
André FelipePrompt Engineering Student

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