Machine Learning Beginner Course
This beginner course introduces core machine learning concepts, focusing on supervised learning techniques, data preparation, model training, evaluation, and optimization 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 splitting, cross-validation, and important measures such as accuracy, precision, recall, and F1 score. Work with Python, NumPy, pandas, and scikit-learn to create logistic regression, k-NN, and decision tree models, develop features, conduct proper experiments, and deliver repeatable, clearly documented outcomes quickly.
Elevify advantages
Develop skills
- Construct ML classifiers: implement logistic regression, kNN, and decision trees efficiently.
- Prepare reliable ML data: apply pandas, encoding, and scaling for strong features.
- Train and assess models: utilise scikit-learn, metrics, and cross-validation.
- Enhance model results: adjust features, address imbalance, and optimise metrics.
- Deliver repeatable ML: organise experiments, fix seeds, and control 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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