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.
Coursera
Embark on a journey through the complete data mining pipeline with this in-depth online course. From initial data understanding to advanced modeling and evaluation, you'll gain a thorough understanding of each critical step involved in transforming raw data into actionable insights. Perfect for aspiring and professional data scientists seeking to refine their expertise.
Coursera
Explore the essential methods of data mining with our expert-led online course. From understanding frequent patterns to advanced techniques like classification and clustering, this course will equip you with the skills needed to analyze complex datasets effectively. Join us now!
Coursera
Embark on an insightful journey into the world of data mining with our Data Mining Project course. This course provides you with the essential skills needed to tackle real-world challenges by designing and executing a complete data mining project from start to finish. Whether you're aiming for academic credit or professional development, this course is your gateway to mastering the art and science of data analysis.