Pattern Recognition Course
This course equips learners with essential skills in pattern recognition for purchase prediction using session-level data, covering data analysis, feature engineering, model building, evaluation, and production deployment.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Pattern Recognition Course teaches you how to examine session-level data, clean and check logs, and create strong features for good purchase prediction. You will make solid preprocessing pipelines, compare supervised models, adjust thresholds, and use business-focused measures. Learn to understand, watch, and explain models clearly so insights lead to real, measurable effects.
Elevify advantages
Develop skills
- Session data analysis: quickly profile, clean and validate large behavioural logs.
- Practical feature engineering: build robust, high-signal features for purchase models.
- ML-ready pipelines: encode, scale and select features with leak-free workflows.
- Model evaluation mastery: choose metrics and thresholds that maximise business KPIs.
- Production ML skills: monitor drift, explain models and ship ethical session AI.
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.What our students say
Your classes are perfect. I purchased the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... I appreciate everything you do, I've already recommended you to others...

Giulio CarloDigital Marketing Student
I like how the lessons are 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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