ML Course
This course provides a practical introduction to machine learning, covering data preparation, modeling, evaluation, and deployment techniques for building reliable predictive models from customer data.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This ML Course gives you a fast, practical path from raw customer data to reliable models. You will learn dataset profiling, EDA, data cleaning, feature engineering, and handling missing values or class imbalance. Build and evaluate baseline models, understand key metrics, improve performance, and plan deployment, monitoring, and explainability so your predictions stay accurate and actionable over time.
Elevify advantages
Develop skills
- Practical ML workflow: design customer-focused prediction pipelines fast.
- Data prep mastery: clean, encode, scale and balance real-world datasets.
- Baseline modeling: build and validate linear and logistic regression quickly.
- Model evaluation: choose metrics, tune thresholds, and read diagnostics.
- Deployment-ready ML: explain models, monitor drift, and run simple A/B tests.
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 opportunity to follow various topics of my interest without needing to change platforms... I'm grateful for everything you do, I've already recommended you to other people...

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 FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.

André FelipePrompt Engineering Student
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