DS 397: Advanced Computational Methods in Data Science

Graduate course, College of Science, University of the Philippines, Diliman

An algorithmic and computational perspective on machine learning and data science methods.

3 units (3 hr/week)

After completing this course, the student should be able to:

Implement common supervised and unsupervised learning algorithms in code via computational executable notebooks.
Understand learning algorithms through existing code implementations.
Solve issues arising from numerical implementations of learning methods.
Evaluate the performance of popular learning algorithms in terms of time and space complexities.
Select the right algorithms for data mining and learning in different cases depending on the available time and computational resouces.
Design new learning algorithms incorporating readable code implementation, good programming practice, sufficient testing, maintenance, and version control.

Please visit this github repo.