Machine Learning Beginner Course
This beginner course introduces core machine learning concepts, focusing on supervised learning techniques, data preparation, model training, evaluation, and reproducible experimentation using Python libraries.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain essential machine learning abilities in this beginner-focused course. You will study supervised classification, train/test splits, cross-validation, and important measures such as accuracy, precision, recall, and F1 score. Practise using Python, NumPy, pandas, and scikit-learn to create logistic regression, k-NN, and decision tree models, develop features, conduct neat experiments, and deliver repeatable, properly recorded outcomes quickly.
Elevify advantages
Develop skills
- Create ML classifiers: use logistic regression, kNN, and decision trees swiftly.
- Ready clean ML data: apply pandas, encoding, and scaling for strong features.
- Train and assess models: employ scikit-learn, metrics, and cross-validation.
- Enhance model performance: adjust features, manage imbalance, and improve metrics.
- Deliver repeatable ML: organise experiments, fix seeds, and handle environments.
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 workload.What our students say
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