Certifications

The Machine Learning with Python certification I earned can be split into two different parts: supervised and unsupervised learning. The supervised learning part was centered around regression algorithms, like linear and logistic regression, as well as regression trees, and classification algorithms, like SVMS, k-NN, and decision trees. It also talked about algorithms like random forests and XGBoost that can be used for both classification and regression. The unsupervised learning part was focused around algorithms like DBSCAN, HDBSCAN, t-SNE, and UMAP.

The certification also covered how to evaluate models using F1 and accuracy for classification, Mean Absolute Error, Mean Squared Error, and Root Mean Squared Error for regression, and heuristics for unsupervised learning algorithms.

To verify the certification, click here.