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.
Monthly Subscription Starting at AED 99 + VAT
- Level Professional
- المدة
- الطبع بواسطة University of Colorado Boulder
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Offered by
عن
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. Data Mining can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder. Specialization logo image courtesy of Diego Gonzaga, available here on Unsplash: https://unsplash.com/photos/QG93DR4I0NEAuto Summary
Unlock the power of data with the "Data Mining Foundations and Practice" course, a comprehensive specialization in IT and Computer Science designed for data science professionals and domain experts. Dive into the fundamental concepts and essential techniques for uncovering patterns within large-scale data sets through a structured learning path. This specialization is divided into three key courses: 1. **Data Mining Pipeline**: Gain a solid understanding of data preprocessing, warehousing, modeling, and evaluation. 2. **Data Mining Methods**: Master techniques such as frequent pattern analysis, classification, clustering, and outlier detection. 3. **Data Mining Project**: Apply your knowledge to a real-world data mining project, enhancing your hands-on skills. Ideal for learners pursuing academic credit, this course can be part of CU Boulder’s Master of Science in Data Science (MS-DS) degree on Coursera. The MS-DS program is interdisciplinary, featuring faculty from Applied Mathematics, Computer Science, Information Science, and more. With performance-based admissions and no application process, it caters to individuals from various educational and professional backgrounds in computer science, information science, mathematics, and statistics. Enroll today and choose from flexible subscription options—Starter and Professional—tailored to meet your learning needs. Whether you're looking to advance your career or expand your expertise, this professional-level course provides the tools and knowledge to excel in the dynamic field of data mining.
Qin (Christine) Lv