Machine Learning Beginner Course
This beginner course introduces essential machine learning concepts, focusing on building, training, and evaluating classification models using Python and scikit-learn.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Master core machine learning skills in this focused beginner course. You will learn supervised classification, train/test split, cross-validation, and key metrics like accuracy, precision, recall, and F1. Practice with Python, NumPy, pandas, and scikit-learn to build logistic regression, k-NN, and decision tree models, engineer features, run clean experiments, and ship reproducible, well-documented results fast.
Elevify advantages
Develop skills
- Build ML classifiers: apply logistic regression, kNN, and decision trees fast.
- Prepare clean ML data: use pandas, encoding, and scaling for robust features.
- Train and evaluate models: use scikit-learn, metrics, and cross-validation.
- Improve model performance: tune features, handle imbalance, and refine metrics.
- Ship reproducible ML: structure experiments, set seeds, and manage environments.
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
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The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.
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