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Machine Learning Applications in HR Course

Machine Learning Applications in HR Course
from 4 to 360h flexible workload
certificate valid in your country

What will I learn?

This Machine Learning Applications in HR Course demonstrates how to set measurable talent objectives, create clean, privacy-conscious datasets, and develop robust features for recruitment, staff retention, and employee engagement. Master the art of selecting and assessing models, minimising bias, presenting results transparently, and converting predictions into actionable steps, dashboards, and trials that enhance decision-making whilst handling risks and compliance requirements.

Elevify advantages

Develop skills

  • Design HR ML pilots: create swift, low-risk trials that demonstrate business benefits.
  • Engineer HR data features: transform ATS and HRIS data into pristine, ML-ready inputs.
  • Evaluate HR models: select metrics that monitor staff turnover, time-to-hire, and uplift.
  • Build fair, private HR AI: implement bias audits, protections, and privacy measures.
  • Turn ML insights into action: direct recruiters and managers with straightforward guides.

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'm grateful 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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