Graduate Certificate in Probabilistic Data Structures
-- ViewingNowThe Graduate Certificate in Probabilistic Data Structures is a specialized course that focuses on advanced techniques for managing and analyzing large-scale data sets. Probabilistic data structures are essential for modern data-intensive applications, enabling efficient processing and analysis of massive data volumes.
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โข &enspace;Introduction to Probabilistic Data Structures&enspace;โ Fundamentals, concepts, and applications of probabilistic data structures.
โข &enspace;Hash Functions & Collision Resolution&enspace;โ Theory, implementation, and evaluation of hash functions, and collision resolution techniques.
โข &enspace;Bloom Filters&enspace;โ Design, analysis, and use cases of Bloom filters.
โข &enspace;Count-Min Sketch&enspace;โ Construction, properties, and applications of Count-Min sketches.
โข &enspace;HyperLogLog&enspace;โ Algorithms, accuracy, and implementations of HyperLogLog for cardinality estimation.
โข &enspace;Probabilistic Tree Data Structures&enspace;โ Overview, advantages, and limitations of probabilistic tree data structures.
โข &enspace;Case Studies of Probabilistic Data Structures&enspace;โ Real-world examples and best practices of probabilistic data structures in industry and research.
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