Certificate in Clustering Analysis: Core Techniques
-- ViewingNowThe Certificate in Clustering Analysis: Core Techniques is a comprehensive course designed to equip learners with essential skills in clustering analysis. This certification program focuses on teaching various clustering techniques, including partitioning methods, hierarchical clustering, density-based methods, and model-based methods.
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โข Introduction to Clustering Analysis: Defining clustering, use cases, algorithms, and evaluation metrics
โข Distance Measures: Understanding and applying various distance measures in clustering
โข Partitioning Methods: K-means, K-medoids, and their variations
โข Hierarchical Clustering: Agglomerative and divisive techniques, linkage criteria, and dendrograms
โข Density-Based Methods: DBSCAN, OPTICS, and their applications
โข Clustering Validation: Internal and external validation methods, and choosing the right number of clusters
โข Dimensionality Reduction for Clustering: PCA, t-SNE, and UMAP
โข Clustering Large Datasets: Sampling, parallelization, and streaming techniques
โข Real-World Applications: Case studies on text mining, image segmentation, and customer segmentation
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