Advanced Data Science (ADS)

The ADS course at the University of Cambridge guides students through the data science pipeline and emphasises the importance of prioritising the motivation and context of data science projects.

Department: Department of Computer Science and Technology

Institution: University of Cambridge

Role: Course Director and Lecturer

Hours: 16

From: November 01, 2024

To: December 03, 2024

As the course director, I designed the ADS course focusing on the alignment between data problems and data science projects through software systems that implement a flexible, scalable, and reusable data science process.

Three phases constitute the data science process: access makes the data available, assess evaluates the data, and address uses the data to find insights. The University’s course description is here, while the full content of the ADS course is available here.

In particular, I lectured on how data science projects should be engineered with a purpose and how to access data as the first step of the data science pipeline.

Lectures

Engineering Data Science

November 06, 2024

In this lecture we explore the intersection between systems engineering principles and data science. This provides a framework that emphasizes the importance of context in addressing modern data science challenges.

Data-Oriented Architectures (DOAs)

November 08, 2024

In this lecture we explore the DOA concept and how designing data-first systems addresses data science pipeline requirements regarding data availability and access.