This course covers the core techniques used in data mining, including frequent pattern analysis, classification, clustering, outlier analysis, as well as mining complex data and research frontiers in the data mining field.
Este curso forma parte de Programa especializado: Data Mining Foundations and Practice
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Programa especializado: Data Mining Foundations and PracticeUniversidad de Colorado en BoulderAcerca de este Curso
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Fechas lÃmite flexibles
Restablece las fechas lÃmite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100Â % en lÃnea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 2 de 3 en
Nivel intermedio
data science professionals or domain experts, some experience working with data, successful completion of Data Mining Pipeline
Aprox. 23 horas para completar
Inglés (English)
SubtÃtulos: Inglés (English)
Qué aprenderás
Identify the core functionalities of data modeling in the data mining pipeline
Apply techniques that can be used to accomplish the core functionalities of data modeling and explain how they work.
Evaluate data modeling techniques, determine which is most suitable for a particular task, and identify potential improvements.
Habilidades que obtendrás
- outlier analysis
- clustering
- classification
- model evaluation
- frequent pattern analysis
Fechas lÃmite flexibles
Restablece las fechas lÃmite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100Â % en lÃnea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 2 de 3 en
Nivel intermedio
data science professionals or domain experts, some experience working with data, successful completion of Data Mining Pipeline
Aprox. 23 horas para completar
Inglés (English)
SubtÃtulos: Inglés (English)
ofrecido por
Universidad de Colorado en Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
Comienza a trabajar para obtener tu maestrÃa
Este curso es parte del Master of Science in Data Science completamente en lÃnea de Universidad de Colorado en Boulder.
Si te aceptan en el programa completo, tus cursos cuentan para tu tÃtulo de grado.
Programa - Qué aprenderás en este curso
6 horas para completar
Frequent Pattern Analysis
This module starts with an overview of data mining methods, then focuses on frequent pattern analysis, including the Apriori algorithm and FP-growth algorithm for frequent itemset mining, as well as association rules and correlation analysis.
6 horas para completar
2 videos (Total 94 minutos), 2 lecturas, 1 cuestionario
6 horas para completar
Classification
This module introduces supervised learning, classification, prediction, and covers several core classification methods including decision tree induction, Bayesian classification, support vector machines, neural networks, and ensemble methods. It also discusses classification model evaluation and comparison.
6 horas para completar
2 videos (Total 106 minutos)
6 horas para completar
Clustering
This module introduces unsupervised learning, clustering, and covers several core clustering methods including partitioning, hierarchical, grid-based, density-based, and probabilistic clustering. Advanced topics for high-dimensional clustering, bi-clustering, graph clustering, and constraint-based clustering are also discussed.
6 horas para completar
2 videos (Total 105 minutos), 1 lectura, 1 cuestionario
5 horas para completar
Outlier Analysis
This module discusses three different types of outliers (global, contextual, and collective) and how different methods may be used to identify and analyze such outliers. It also covers some advanced methods for mining complex data, as well as the research frontiers of the data mining field.
5 horas para completar
2 videos (Total 108 minutos)
Acerca de Programa especializado: Data Mining Foundations and Practice
The Data Mining specialization is intended for data science professionals and domain experts who want to learn the fundamental concepts and core techniques for discovering patterns in large-scale data sets. This specialization consists of three courses: (1) Data Mining Pipeline, which introduces the key steps of data understanding, data preprocessing, data warehouse, data modeling and interpretation/evaluation; (2) Data Mining Methods, which covers core techniques for frequent pattern analysis, classification, clustering, and outlier detection; and (3) Data Mining Project, which offers guidance and hands-on experience of designing and implementing a real-world data mining project.
Preguntas Frecuentes
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