Overview

Extracting meaningful insights from massive datasets and constructing intelligent autonomous systems is central to driving modern technological innovation, economic growth, and decision-making across global industries. The BSc (Hons) Artificial Intelligence and Data Science at University of Derby delivers a rigorous technical education focused on the mathematical frameworks, computational mechanisms, and analytical tools required to design advanced AI models. Taught by research-active academics within the Department of Computing and Mathematics, the curriculum integrates core computer science foundations with specialized instruction in statistical inference, machine learning, predictive modeling, and data visualization. Students hone their practical skills in cutting-edge computing laboratories, including the CAVE lab for immersive 3D data rendering, specialized cross-reality suites, and creative prototyping spaces. The degree places a strong emphasis on practical application and industry engagement, offering flexible transfer options across the computing portfolio alongside optional placement year opportunities. This course is ideally suited for mathematically minded, analytical problem-solvers who are eager to build algorithmic systems, solve complex data challenges, and pioneer intelligent technologies.

What You'll Learn

• Fundamental mathematical principles of data analysis, linear algebra, probability theory, calculus, and statistical inference

• Core concepts of artificial intelligence, search algorithms, knowledge representation, and logical reasoning architectures

• Machine learning methodologies, supervised and unsupervised learning algorithms, deep learning models, and neural network construction

• Computer programming paradigms, software design, algorithmic thinking, and efficient data structure implementation

• Large-scale data processing techniques, database systems design, data mining protocols, and predictive analytics modeling

• Specialized data visualization methods, exploratory data analysis, and advanced graphical rendering using high-tech laboratory environments

• Collaborative software engineering principles, project management, and ethical considerations in AI development and data privacy

• Practical problem-solving applications using real-world case studies, employer-led projects, and industry-standard computational tools

• Independent final-year individual capstone project applying research methodologies and innovative AI solutions to complex practical scenarios

Learning Outcomes

Graduates will possess an in-depth understanding of the mathematical foundations, statistical theories, and software architectures underlying modern artificial intelligence and data science. They will demonstrate the capability to extract, clean, analyze, and interpret complex structured and unstructured datasets to derive actionable insights for business and scientific applications. Students build strong practical capabilities in programming languages, machine learning framework implementation, statistical software utilization, and data visualization technique execution through hands-on laboratory work and project-based assessments. Furthermore, scholars master the ability to critically evaluate the ethical, security, and regulatory implications of autonomous systems, effectively communicating technical analytical models and data-driven insights to both technical specialists and non-expert stakeholders. Through portfolio development, collaborative industry projects, and independent capstone research, graduates cultivate the technical precision and problem-solving agility needed to excel as data scientists, machine learning engineers, data architects, business intelligence analysts, or quantitative technology consultants across diverse commercial sectors.