Bill Howe

Bill Howe is the Director of Research for Scalable Data Analytics at the UW eScience Institute and holds an Affiliate Assistant Professor appointment in Computer Science & Engineering, where he leads a group studying data management, analytics, and visualization systems for science applications. Howe has received awards from Microsoft Research and honors for papers in scientific data management, and serves on a number of program committees, organizing committees, and advisory boards in the area, including the advisory board of the Data Science certificate program at UW. He holds a Ph.D. in Computer Science from Portland State University and a Bachelor's degree in Industrial & Systems Engineering from Georgia Tech.

Coursera

University of Washington

Communicating Data Science Results (Coursera)

Statistics & Data Analysis Data Science

Unlock the secrets of effective communication in data science! This course teaches you how to interpret your results accurately, present them clearly, and use powerful visualization techniques to inform business decisions. Whether you're a seasoned professional or just starting out, our expert-led sessions will equip you with the skills needed to make your insights impactful.

Jun 22nd 2026

3 Weeks

Ethics Cloud Computing Privacy

Coursera

University of Washington

Data Manipulation at Scale: Systems and Algorithms (Coursera)

Statistics & Data Analysis Data Science

Dive into the world of big data analytics with 'Data Manipulation at Scale: Systems and Algorithms'. This course will equip you with the knowledge and skills needed to effectively manage, analyze, and manipulate large volumes of data using cutting-edge systems and algorithms. Learn how to harness powerful computing resources and programming abstractions to extract valuable insights from complex datasets.

Jun 22nd 2026

4 Weeks

Algebra Algorithms Databases

Coursera

University of Washington

Practical Predictive Analytics: Models and Methods (Coursera)

Statistics & Data Analysis Data Science

Dive into the world of data science with 'Practical Predictive Analytics: Models and Methods'. This course is designed for those eager to learn how to design statistical experiments, analyze results using advanced techniques, and avoid common misinterpretations in big data. Gain a core understanding of practical machine learning methods and apply them to real-world problems.

Jun 22nd 2026

4 Weeks

Machine Learning Models Methods

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