Reference Material
Foundational concepts of data mining, covering objectives, methodologies, and the role of data mining in modern analytics and decision-making systems.
View CourseComprehensive study of data representation techniques, manipulation methods, processing workflows, and analytical approaches for extracting insights from complex datasets.
View CourseIn-depth exploration of pattern recognition, data mining tasks including classification and clustering, and fundamental algorithms like decision trees, k-means, and association rules.
View CourseAdvanced machine learning with artificial neural networks, deep learning foundations, ethical considerations in data usage, privacy concerns, and responsible AI practices.
View CourseSemantic web technologies, RDF frameworks, SPARQL queries, and leveraging linked open data for knowledge discovery and data integration across heterogeneous sources.
View CourseComprehensive collection of hands-on data mining exercises covering clustering algorithms, classification techniques, neural network implementations, and real-world dataset analysis.
View on GitHub