BSc (Hons) Computer Science (Artificial Intelligence)

Program Overview

It blends core computer science concepts with specialized AI training, equipping graduates with the skills to design, implement, and evaluate AI systems for real-world problem-solving. The program emphasizes practical experience, research opportunities, and industry-relevant skills, preparing graduates for successful careers in the rapidly evolving field of AI.

Program Outline

Degree Overview:

This BSc (Hons) Computer Science (Artificial Intelligence) degree is designed to provide students with a comprehensive understanding of artificial intelligence (AI) and its applications within the broader field of computer science. It blends a strong foundation in core computer science principles with specialized training in AI, equipping graduates with the skills and knowledge needed for successful careers in this rapidly evolving field. The course aims to:

• Provide students with a thorough understanding of the principles and practices of artificial intelligence.
• Develop students' ability to design, implement, and evaluate AI systems.
• Equip students with the skills needed to apply AI to solve real-world problems.
This program emphasizes practical experience, with opportunities for students to work on projects and develop their programming skills. Students are also encouraged to explore research opportunities and engage with the department's internationally acclaimed AI research staff.

Outline:

The program is structured over three years (or four years with a placement or study abroad year), progressively building upon core computer science concepts and leading students into specialized AI modules.

Year 1:

• Introduction to Programming and Discrete Structures: This module introduces students to programming concepts, problem-solving skills, and fundamental mathematical structures relevant to programming.
• From Silicon To C: This module delves into the principles and organization of computer systems, helping students understand the relationship between hardware and software.
• Operating Systems and Networks: This module covers the fundamentals of operating systems and network design, installation, and configuration.
• Accessibility and Usability: This module examines the accessibility and usability of computing applications, considering legal, social, and ethical issues.
• Artificial Intelligence: This module introduces the basic concepts, paradigms, methods, and algorithms of AI, enabling students to program basic AI systems.
• Computing Things: This module explores the Internet of Things (IoT), focusing on device architecture, sensor data acquisition, and communication protocols.
• Database Systems: This module expands upon relational databases, introducing other database paradigms like NoSQL and graph databases.
• Principles and Practices of Large-Scale Programming: This module covers object-oriented programming techniques, design principles, and large-scale software development practices.

Year 3 (or Year 4 with Placement/Study Abroad):

• Advanced Artificial Intelligence: This module delves into advanced AI concepts, methods, and algorithms for developing complex AI systems.
• Intelligent Adaptive Systems: This module explores Intelligent Adaptive Systems (IAS), including their design and implementation.
• Responsible Computing: This module examines the ethical, legal, and societal implications of computing and technology.
• Social and Collective Artificial Intelligence: This module covers AI systems that exhibit social and collective intelligence, enabling agents to interact and collaborate.
• Software Architecture: This module explores software architecture design patterns and their application in real-world systems.
• Artificial Intelligence Project: This module culminates in an individual project, allowing students to apply their knowledge and skills to a specific AI problem.
• Optional Modules: Students can choose from a range of elective modules, including Machine Learning and Neural Computing, Advanced Database Topics, Information Security Management, Robotics, and more.

Assessment:

Assessment methods vary throughout the program and may include:

• In-class tests: Evaluate students' understanding of core concepts and theories.
• Exams: Comprehensive assessments covering a broader range of topics and skills.
• Coursework: Practical assignments, reports, and projects that demonstrate students' ability to apply their knowledge.
• Project work: Individual or group projects that allow students to undertake in-depth research or develop innovative AI solutions.

Teaching:

Teaching methods employed in the program include:

• Lectures: Provide a comprehensive overview of core concepts and theories.
• Tutorials: Smaller group sessions for interactive learning, problem-solving, and discussion.
• Practicals (labs): Hands-on exercises and experiments to develop programming skills and practical application of theoretical concepts.
• Self-study: Encourage independent learning and exploration of topics beyond the structured curriculum.
The program is taught by highly qualified staff, many with PhDs and significant research and teaching experience. Students benefit from the expertise of the School's internationally acclaimed AI research staff.

Careers:

Graduates of this program are well-equipped for careers in various sectors, including:

• Software engineering: Developing AI-powered applications and systems.
• Data science: Analyzing and interpreting large datasets to extract insights and build predictive models.
• Machine learning: Creating algorithms and models for learning from data.
• Robotics: Designing, developing, and implementing robotic systems with AI capabilities.
• Research: Contributing to the advancement of AI through academic research and development.
Previous graduates have secured roles at prestigious companies like BAE Systems, NHS, EE, Intel, IBM, and BT.

Other:

• The program is located at the College Lane campus, which also houses creative arts, science, and health-related subjects.
• Students have access to well-equipped laboratory facilities with PCs running Windows 11 and Linux, along with industry-standard software.
• The university provides extensive learning resources, including 24/7 open Learning Resource Centres, Studynet (online study environment), and open access to labs.
• The new School of Physics, Engineering and Computer Science building, opening in 2024, will feature a variety of experiential learning zones, including robotics labs, UX empathy labs, and research spaces.
• The university offers support services, such as the Success and Skills Support Unit, which provides employability and academic skills development, and access to industry mentors.
This BSc (Hons) Computer Science (Artificial Intelligence) program offers a comprehensive and practical approach to AI education, preparing graduates for successful careers in this rapidly growing field.

UK Students Full time £9250 for the 2024/2025 academic year EU Students Full time £15500 for the 2024/2025 academic year International Students Full time £15500 for the 2024/2025 academic year