AFDS: Algorithmic Foundations of Data Science

Welcome to Algorithmic Foundations of Data Science!

Learning Outcomes

On completion of this course, the student will be able to:

1. demonstrate familiarity with fundamentals for processing massive datasets.
2. describe and compare the various algorithmic design techniques covered in the syllabus to process massive datasets
3. apply the learned techniques to design efficient algorithms for massive datasets
4. apply basic knowledge in linear algebra and probability theory to prove the efficiency of the designed algorithm
5. use an appropriate software to solve certain algorithmic problems for a given dataset

The course aims to introduce algorithmic techniques that form the foundations of processing and analysing massive datasets of various forms. In particular, the course discusses how to pre-process massive datasets, efficiently store massive datasets, design fast algorithms for massive datasets, and analyse the performance of designed algorithms. Through various examples and the coursework, the students will see applications of the topics discussed in class in other areas of computer science, e.g., machine learning, and network science.