BSc (Hons) Data Scientist (Integrated Degree

This module is an introduction to networking and networking operating systems where you'll identify key components of a network system and their operating system. You'll gather basic understanding of networking protocols and be able to set up and troubleshoot hardware and software problems.

Developing high-quality software requires more than just coding skills. This practical module explores a wide range of software engineering techniques and industry practices, designed to promote the production of high-quality, efficient, reliable, and secure software.

You'll be introduced to algorithms with a focus on Sorting (e.g. bubble, quick, heap), Searching (e.g. breadth first and depth first), and Merging (e.g. Simple and K-way).

In this module, you'll be able to identify organisational information requirements and model data solutions using conceptual data modelling techniques.

You'll develop skills in designing and implementing a database solution using industry-standard database management systems. You'll also learn to perform database administration tasks, manage data effectively, and discover the key concepts of data quality and data security. You'll also understand how organisations can use data analytics to support them in making decisions by using data dashboards as an example.

This module introduces the fundamental mathematical and statistical concepts essential for data science. You'll gain a solid foundation in linear algebra, calculus, probability, and statistical methods, which are crucial for understanding and applying data science techniques.

The module is delivered in a practical environment with exposure to a range of real practical applications where mathematical and statistical techniques are used and deployed in data science areas. Specific software such as (but not limited to) MATLAB, SimuLink, Python, and R Studio will be used to test and evaluate models and techniques.

In this module, you'll develop knowledge and understanding of agile and DevOps within modern software development, building on previous software development skills attained. You'll design, develop, and test a software product which you'll then deploy.

This module enables you to work with other apprentices on a project to develop an application for a charity or company. You'll work together on the project from start to finish, through the development life cycle. The project will be assessed as a group and individually, with marks recorded for the group assessment being peer reviewed.

This advanced module delves into the intricacies of big data analytics and advanced visualisation techniques, preparing you to tackle complex data challenges in real-world scenarios. You'll explore cutting-edge technologies and methodologies for handling large-scale datasets, alongside mastering advanced visualisation tools to extract meaningful insights and communicate data-driven narratives effectively.

This module provides a comprehensive introduction to the essential techniques and tools for virtualisation and the infrastructure that supports data scientists. You'll learn how to effectively virtualise computing resources and understand the technological frameworks that enable efficient management.

This final year module is an introduction to Artificial Intelligence (AI), looking at a range of AI techniques and how they can be used to solve problems with society, industry, and research. The development of AI and programming languages over the years have supported industry with decision making.  

In this module, you'll design, develo,p and implement a work-based project on a topic agreed with your employer and University tutor. The project should be based on a data science solution that forms part of your role. The work-based project will inform the report to be completed during the EPA module. On completion, you must provide a signed statement to confirm it's your own work.

This module also encourages you to develop a set of professional skills, such as problem solving, creativity, critical thinking, hypothesis generation and testing, action planning and decision making, self-reflection, organisation and time management, initiative and self-motivation, end-user awareness, presentation skills, and technical report writing for technical and non-technical audiences.

During the module, you'll collate your portfolio of evidence which will support you with your professional discussion within your End Point Assessment.

In this module, you'll undertake the End Point Assessment (EPA), the final stage of the course. This module follows the national requirements and guidance set out in the EPA Plan.

The EPA has three assessment methods: a knowledge test, a report (based on a work-based project), and a professional discussion (informed by a portfolio).