Di Wu

Professor Wu’s primary interests are in temporal databases, the semantic web and data science. Most of his research has been in extending the Resource Description Framework (RDF) for temporal dimensions. Before joining CU, he taught algorithms and data structures, programming languages, and database management courses.

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Association Rules Analysis (Coursera) Coursera
University of Colorado Boulder

Association Rules Analysis (Coursera)

Statistics & Data Analysis Data Science

Dive into the world of unsupervised learning with our comprehensive Association Rules and Outliers Analysis course. This course is designed to equip you with essential skills in identifying patterns within large datasets using association rules and detecting anomalies through advanced techniques. Whether you're a data enthusiast or a professional looking to enhance your analytical toolkit, this course offers practical knowledge and real-world applications.

Jun 22nd 2026
5-12 Weeks
Data Mining Unsupervised Learning Coursera Plus
Details
Data Analysis with Python Project (Coursera) Coursera
University of Colorado Boulder

Data Analysis with Python Project (Coursera)

Statistics & Data Analysis Data Science

Embark on a practical journey into the world of data analysis with our 'Data Analysis with Python Project' course. This hands-on specialization will guide you through applying your skills to a real-life project, exploring various analytical methods and techniques using Python. From raw data to actionable insights, this course is designed for those who want to make informed decisions based on data.

Jun 22nd 2026
5-12 Weeks
Python Machine Learning Clustering
Details
Data Wrangling with Python Project (Coursera) Coursera
University of Colorado Boulder

Data Wrangling with Python Project (Coursera)

Statistics & Data Analysis Data Science

Embark on a comprehensive journey through data wrangling with our hands-on 'Data Wrangling with Python Project' course. This course is designed to equip you with the essential skills needed to navigate the complex world of data processing. By following a real-life project, you'll learn how to identify and source data, clean it, integrate various datasets, and prepare them for analysis using Python. Whether you're new to data science or looking to refine your existing skills, this course offers practical experience that's crucial in today's data-driven world.

Jun 22nd 2026
5-12 Weeks
Python Data Mining Data Wrangling
Details
Classification Analysis (Coursera) Coursera
University of Colorado Boulder

Classification Analysis (Coursera)

Statistics & Data Analysis Data Science

Dive into the 'Classification Analysis' course and unlock a deep understanding of how to classify data using various powerful algorithms. This comprehensive course on Coursera will guide you through key classifiers like K-Nearest Neighbors (KNN), Decision Trees, Support Vector Machines (SVM), Naive Bayes, and Logistic Regression. You'll gain practical experience by applying these techniques to actual datasets, enhancing your ability to perform data analysis effectively.

Jun 22nd 2026
5-12 Weeks
Classification Logistic Regression Support Vector Machines
Details
Clustering Analysis (Coursera) Coursera
University of Colorado Boulder

Clustering Analysis (Coursera)

Statistics & Data Analysis Data Science

Dive into the world of unsupervised learning with our comprehensive 'Clustering Analysis' course on Coursera. This course is designed to equip you with essential knowledge and practical skills in clustering techniques and dimension reduction, enabling you to effectively analyze and interpret complex datasets. Whether you're a data enthusiast or a professional looking to advance your career, this course offers valuable insights into the unsupervised learning landscape.

Jun 22nd 2026
5-12 Weeks
Clustering PCA Clustering Analysis
Details
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