Introduction To Machine Learning Course
This course provides a practical introduction to machine learning, focusing on churn and return prediction, data preparation, model building, evaluation, and deployment.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This short, practical Introduction to Machine Learning Course guides you through framing churn and return prediction problems, exploring and cleaning real-world data, and building reliable models. You will learn feature engineering, encoding, handling imbalance, cross-validation, tree-based methods, calibration, fairness checks, and deployment-ready reporting so you can ship models that drive measurable business impact.
Elevify advantages
Develop skills
- Business-first ML framing: turn churn and return goals into clear ML tasks.
- Fast data prep: clean, encode, and balance real customer datasets for ML.
- Practical model training: tune, validate, and compare tree and linear models.
- Applied evaluation: pick metrics, set thresholds, and check fairness by segment.
- Deployment-ready ML: build pipelines, monitor drift, and report results clearly.
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
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