Qin (Christine) Lv

Qin (Christine) Lv is an Associate Professor and Co-Associate Chair for Graduate Education in the Department of Computer Science, University of Colorado Boulder. She received her PhD degree in computer science from Princeton University. Lv's research focuses on full-stack data analytics, which integrates systems, algorithms, and applications for effective and efficient data analytics in ubiquitous computing and scientific discovery. Her research is interdisciplinary in nature and interacts closely with a wide range of scientific domains as well as many user-orientated applications. Lv has received many awards, including the SenSys 2018 Best Paper Runner-up Award, 2017 Google Faculty Research Award, and VLDB 2017 Ten Year Best Paper Award.

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Data Mining Project (Coursera)

This course offers step-by-step guidance and hands-on experience of designing and implementing a real-world data mining project, including problem formulation, literature survey, proposed work, evaluation, discussion and future work. Data Mining Project can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science [...]
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Data Mining Methods (Coursera)

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. Data Mining Methods can be taken for academic credit as part of CU Boulder’s Master of Science [...]
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Data Mining Pipeline (Coursera)

This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehousing, data modeling, interpretation and evaluation, and real-world applications. Data Mining Pipeline can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree [...]
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