The Data Science Design Manual Course


Course Information

This course is based on the Data Science Design Manual by Professor Steven Skiena who is the Distinguished Teaching Professor of Computer Science at Stony Brook University.

The course follows the topics in the book and includes slides and video lectures by Professor Steven Skiena and his team. We highly recommend that you buy the book to follow through the slides and video lectures.

Course License: CC BY-NC-SA 4.0

Additional resources including data sets for projects and assignments can be found at the website of the book. (

From the book website:

The Data Science Design Manual serves as an introduction to data science, focusing on the skills and principles needed to build systems for collection, analyzing, and interpreting data. As a discipline data science sits at the intersection of statistics, computer science, and machine learning, but it is building a distinct heft and character of its own.

The book covers enough material for an "Introduction to Data Science" course at the undergraduate or early graduate student levels.

The course is designed to provide a hands-on introduction to Data Science by challenging student groups to build predictive models for upcoming events, and validating their models against the actual outcomes.

The video and lecture slides are from my Fall 2016 Data Science (CSE 519) course.

Structure Overview and Typical Completion Time

This course consists of 19 modules and 27 videos.

The estimated course learning time is about 40 hours.

Programme Support

For content questions, please reach out to our community at our forum.

For technical issues, contact us here.

AI Singapore would like to thank Professor Steven Skiena for allowing us to use his materials, including videos lectures and notes to build a course for AI Singapore members.

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