Python Machine Learning Course - Learn Python Machine Learning Online

Understand machine learning — Know what ML is, when to use it, and how it differs from writing rules by hand
Work with data confidently — Handle arrays, DataFrames, and mixed data types including numerical, categorical, and ordinal
Describe any dataset statistically — Calculate and interpret mean, median, mode, standard deviation, variance, and percentiles
Visualise data like a pro — Build histograms, normal distributions, and scatter plots to spot patterns before training any model
Build regression models — Fit and evaluate linear, polynomial, and multiple regression models using SciPy, NumPy, and scikit-learn
Scale features for fair comparison — Apply standardisation so every input variable competes on equal terms inside your model
Evaluate models honestly — Split data into training and testing sets, measure R-squared, and diagnose overfitting before it ships
Build decision trees — Grow, read, and predict with classification trees that produce transparent, explainable decisions from data

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