BSc (Hons) Data Science

Overview

The graduate apprenticeship programme is open to new or existing employees in Scotland of all ages and consists of 20% academic learning and 80% work-based learning.

This graduate apprenticeship programme aims to combine core elements of all these areas. Successful completion of this programme will allow the graduate to become a graduate data science engineer, enabling their company or employer to benefit from up to date knowledge in this area.

Graduates' skillset

The Data Science graduate apprenticeship programme aims to produce BSc (Hons) graduates who:

• have an understanding of their organisations data strategy and why it's important
• are able to source, collect and integrate data;
• have an awareness of techniques such as machine learning, data mining, prescriptive and predictive analytics (trends and patterns), and forecasting;
• have an understanding of the different types of quantitative research methods and statistical techniques for analysing data such as hypothesis testing, standard deviation, regression and correlation;
• have an understanding of the principles and advantages of machine learning and applying learning algorithms to data;
• have an understanding of the different specialist data analytical tools and how they can be used to support decision making;
• are able to demonstrate how data science can be applied to improve their organisation's processes, operations and outputs;
• are able to demonstrate the different ways of communicating meaning from data;
• have an understanding of how data science operates within the context of data governance and data security;
• have an understanding of a range of contemporary project management methods and their differences;
• are able to operate in team and multidisciplinary contexts.

Key areas of the programme

The primary focus of the Data Science graduate apprenticeship programme is on developing the knowledge, understanding and skills outcomes sought by employers.

Business

• Business functions, behaviours, ethics, and courtesies
• Business strategy and management

Technology

• Software development essentials
• Data and algorithms
• Database systems
• Data Security
• Engineering management
• Machine Learning
• Artificial Intelligence
• Probability and Statistics
• Software modelling and analysis
• Software design
• Software development process
• Data modelling, database development, and data analysis
• Protection and Ethics

Personal and interpersonal

• Communications
• Personal attributes
• Professional attributes
• Team working

Data project and delivery management

• Project management methodologies
• Project planning
• Project execution
• Agile project delivery
• Risk assessment and management