Data Science

Applied Statistics for Data Science
This module explores data acquisition and statistical analysis techniques crucial for data
scientists in various industries. It emphasizes the development of soft skills in effectively
communicating results, a vital aspect for business stakeholders. The practical applications span across diverse sectors such as financial services, healthcare, and manufacturing, providing a well-rounded foundation for real-world data science challenges. 

Data Mining and Statistical Forecasting
This module delves into the essential tools and techniques employed for Data Mining and Statistical Modelling. Data mining enables organizations to extract valuable insights from unstructured text data, facilitating informed decision-making based on user feedback and other data sources. Statistical modelling and forecasting play a critical role in predicting future trends, particularly in the financial sector. The module incorporates class case studies, exercises, and assignments that offer valuable context and practical experience in industries reliant on these techniques.

Project Management and Research Methodology
This module equips students with essential skills for independently undertaking and
managing research projects. It focuses on crucial aspects of research, including conducting literature reviews and honing research and writing skills. By mastering these fundamentals, students are well-prepared to embark on their own research projects, fostering a strong foundation in research methodology and project management.

MSc Research Project
In this module, students embark on an independent research project, which may involve
collaborations with companies, staff-proposed research proposals, or student-generated ideas. For full-time students, the project spans a single 12-week block, while part-time students have two 12-week blocks. This module provides students with the opportunity to showcase their research, enabling them to demonstrate their expertise and contribute valuable insights to their chosen field of study.

Principles of Computing
This module introduces students to the fundamentals of database management systems, including SQL and Oracle, which are highly esteemed in the industry. Additionally, it offers a broader overview of general-purpose programming languages. Through this module, students acquire essential skills and knowledge in database management and programming, setting a strong foundation for their career in Data Science.

Applied Machine Learning and Deep Learning
In this module, students dive into the data-driven analysis of real-world datasets using
supervised and unsupervised modelling techniques. The applications span a wide range of industries, including finance, manufacturing, healthcare, and autonomous vehicles.

Big Data Engineering and its Applications
This module delves into the tools and techniques essential for handling massive volumes of structured and unstructured data. Students gain practical insights into the role of a Data Engineer, with hands-on experience in cloud computing frameworks like Amazon Web Services (AWS) through our affiliation with the AWS Academy program. This prepares students to effectively manage and manipulate data in real-world scenarios, making them valuable assets in the era of big data.

MSc Research Project
In this module, students embark on an independent research project, which may involve
collaborations with companies, staff-proposed research proposals, or student-generated ideas. For full-time students, the project spans a single 12-week block, while part-time students have two 12-week blocks. This module provides students with the opportunity to showcase their research, enabling them to demonstrate their expertise and contribute valuable insights to their chosen field of study.