Machine Learning with Python Certification Training

Machine Learning with Python teaches you how to turn labelled and unlabelled data into models that predict, classify and group. The course is code-first: for each algorithm you learn the intuition, the maths you need to understand its behaviour, and how to apply it with scikit-learn on real datasets.

Beyond individual algorithms, the emphasis is on doing machine learning correctly. You learn to build preprocessing pipelines, split data without leakage, compare models with cross-validation, tune hyperparameters, handle imbalanced classes, explain predictions with feature importance and SHAP, and monitor for drift at a conceptual level. Gradient boosting libraries such as XGBoost and LightGBM are included because they dominate tabular problems in industry.

There is no external exam. You finish with a capstone model and an Assure Success course-completion certificate. Deep learning and LLMs are covered in separate courses.