Machine Learning in Marketing Course
This course equips marketers with practical machine learning skills to enhance campaigns, segment customers, predict behaviors, and measure business impact through data-driven strategies.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Machine Learning in Marketing Course teaches you how to link KPIs with actual business results, understand benchmarks, and transform data into focused actions. You will learn to prepare and assess data, grasp important models such as propensity, segmentation, and recommendations, and incorporate ML insights into campaigns using clear testing strategies, risk management, and measurable revenue effects in a short, hands-on way.
Elevify advantages
Develop skills
- ML-powered segmentation: build high-value fashion customer clusters quickly.
- Propensity modeling: use churn and purchase scores to launch smart campaigns.
- Data-ready marketing: check CRM and channel data for ML-ready quality.
- KPI-driven testing: design A/B and uplift tests to demonstrate ML revenue impact.
- Workflow integration: integrate ML scores into email, ads, and onsite personalization.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workloadWhat 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 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 FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!

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 CarloPrompt Engineering Student
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