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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.
Clustering helps businesses discover hidden segments in their data — such as customer groups or market segments — enabling more targeted strategies.
An e-commerce company uses clustering to group customers by purchasing behaviour, then tailors marketing campaigns to each segment.
Unsupervised Learning
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.
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.
Dataset
A dataset is a structured collection of data used to train, validate, or test a machine learning model. It can consist of text, images, numbers, audio, or any other type of information, typically organised into rows and columns or files and labels.
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.