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Unsupervised learning is a type of machine learning where the model is trained on data without labelled answers. The model discovers hidden patterns, groupings, and structures in the data on its own, without being told what to look for.
Unsupervised learning is invaluable when labelled data is expensive or unavailable — it helps uncover insights you did not know to look for.
A bank uses unsupervised learning to detect unusual transaction patterns that might indicate fraud, without needing a pre-labelled set of fraudulent transactions.
Supervised Learning
Supervised learning is a type of machine learning where the model is trained on labelled data — input-output pairs where the correct answer is provided. The model learns to map inputs to outputs and can then predict the correct output for new, unseen inputs.
Clustering
Clustering is an unsupervised learning technique that groups similar data points together without predefined labels. The algorithm discovers natural patterns and structures in the data based on similarity measures.
Dimensionality Reduction
Dimensionality reduction is a technique that simplifies complex data by reducing the number of variables (dimensions) while preserving as much meaningful information as possible. It helps make high-dimensional data easier to visualise, analyse, and process.
Our programme follows a structured Level 4 curriculum with project-based learning, practical workflows, and guided implementation across business and career use cases. Funded route available for UK citizens and ILR holders.