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Feature Engineering Course

What will I learn?

Unlock di power wey dey inside data wit our Feature Engineering Training, design for engineering professionals dem wey sabi book well well and wey want make dem predictive modeling skills strong pass before. Enter inside di deep of advanced techniques like how to handle categorical variables, time-based engineering, and how to make data small. Learn how to explore dataset, create features, and write am down well well. Learn how to use Python, Pandas, and Scikit-learn for real work. Check how features dey affect model performance and make decisions based on data wit confidence. Join now so dat you go change di way you see data!

Apoia's Unique Features

Online course accessible for life
Certificate compliant with educational standards
Printable PDF summaries
Online support always available
Select and arrange the chapters you wish to study
Set your own course workload
Instant feedback on practical activities
Study at your convenience, without needing internet access

Develop skills

Strengthen the development of the practical skills listed below

Learn how to handle categorical variables well well so dat you go get strong data models.

Use time-based feature engineering so dat you go understand data wey dey change over time.

Learn how to make data small so dat your model go dey fast.

Learn how to make features work togeda so dat you go predict things correct.

Use Python libraries so dat you go engineer features well well.

Suggested summary

Workload: between 4 and 360 hours

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

Examples of chapters you can add

You will be able to generate more chapters like the examples below

This is a free course, focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but offers practical and relevant knowledge for your professional journey.