📖Program Curriculum
This Data Science course is composed of a combination of modules that cover a broad range of data science methods, applications, and foundations.
In the first semester, you will study two 30-credit modules which aim to introduce you to data science, provide you with an opportunity to develop skills in computer programming, build expertise in data analysis, and establish mathematical foundations. Additional one-to-one support is available through the Sigma Mathematics and Statistics Support Centre (subject to availability).
In the second semester, you will study four 15-credit modules which aim to broaden your knowledge in the application areas in information retrieval, data management systems, machine learning and big data. These modules respond to different challenges in data management and data analysis. Within these modules, a wide range of types and scales of data and data analysis methods will be introduced and applied, from supervised and unsupervised learning to the analysis of text documents.
In the final semester, you will be expected to apply the knowledge and skills you have learned in the first two semesters by undertaking an in-depth individual Data Science project. This may be on some current issue or challenging application in data science and could be industry-based or undertaken in collaboration with one of the university research groups. Guided by a university tutor, this project helps you to develop your research and practical skills while also gaining professional Data Science experience.
Modules
Programming for Data Science - 30 credits
Principles of Data Science - 30 credits
Big Data Analytics and Data Visualisation - 15 credits
Data Management Systems - 15 credits
Information Retrieval - 15 credits
Machine Learning - 15 credits
Global Professional Development – Entrepreneurial Practice - 10 credits
Data Science Project - 50 credits
We regularly review our course content, to make it relevant and current for the benefit of our students. For these reasons, course modules may be updated.