Master classical ML algorithms. Build Regression, Classification, and Clustering models using Scikit-Learn to solve predictive business problems.
Before Deep Learning, you must master Machine Learning. This course covers the essential algorithms used in business today. You will learn Linear and Logistic Regression for prediction, Decision Trees and Random Forests for classification, and K-Means for clustering data. We cover the entire pipeline: data preprocessing, feature scaling, model training, and evaluation metrics (Accuracy, Precision, Recall). By the end, you will be able to deploy a predictive model to a web API.
Estimated completion time: 21 lessons • Self-paced learning • Lifetime access
No, this covers Classical ML (the foundation).
We explain concepts intuitively, libraries do the math.
Yes, predicting churn and customer segmentation.
No, Scikit-Learn is the tool for classical ML.
3 recommended paths based on what you're learning
AI Product Strategist is the career move most Machine Learning A-Z learners don't see coming.
This unexpected skill — Data Ethics — makes your Machine Learning A-Z work twice as effective.
Skip the repetitive parts. Hugging Face AutoTrain helps you fine-tune models without writing code.