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Studying data mining is much more than learning how to analyze data as it helps students to understand the algorithms and techniques that power many of the intelligent technologies we use every day. This includes Netflix recommending your next favourite movie to banks detecting fraudulent transactions and online stores suggesting products you might like.  At its core, data mining is the process of identifying meaningful patterns, trends, and relationships from large datasets. As students explore this field, they gain hands-on  knowledge of how different algorithms solve different types of problems. For example,  classification algorithms are used to categorize data, clustering techniques group similar data points together, regression algorithm predicts future outcomes based on historical data, and association rule mining identifies relationships between different variables such as products frequently purchased together.   Studying these techniques also helps stu...

Have you ever wondered how Netflix recommends your next favorite show, Spotify creates the perfect playlist, or Google predicts what you’re about to search? The answer is machine learning (ML), a technology that powers computers to learn from data and make good decisions. As AI continues to reshape industries, developing knowledge about the basics of machine learning has become a productive skill for every student.  Supervised learning- learning from examples   The algorithm is trained to utilize labelled data, where the correct answers are already provided, and it is commonly used for tasks such as predicting house prices, detecting spam emails, and classifying images.  Unsupervised learning- finding hidden patterns  What happens when there is no answer to learn from? That’s where unsupervised learning stands out: algorithms using labelled data look for patterns and relationships on their own. Businesses use this technique to group customers with similar interests, ...