Computer Science with Artificial Intelligence with Foundation Year BSc(Hons)

4 Years On Campus Bachelors Program

University of Huddersfield

Program Overview

This degree is perfect if you’re eager to start your journey into computer science and artificial intelligence, even if you need a foundation year to build up your skills first. You’ll learn how to create intelligent systems, understand how machines “think,” and explore real-world applications from robotics to AI-powered apps — all while developing strong programming and problem-solving abilities.

Curriculum Structure

Foundation Year
The first year helps you get ready for the main degree. You’ll build core skills in mathematics, computing basics, and computational thinking. By the end of this year, you’ll feel confident with programming, logic, and problem-solving — the essential foundations for computer science.

Year 2
Here’s where the degree really begins! You’ll dive into procedural programming, algorithms and data structures, and databases and web integration. This year is about applying your coding skills, understanding how systems work, and learning how to handle and structure data effectively.

Year 3 (and optional Year 4 placement)
This is your chance to specialise in AI. You’ll study modules like Introduction to Artificial Intelligence, Data-Driven AI, and Knowledge-Based AI. You’ll learn about machine learning, neural networks, and symbolic AI, and work on a substantial project to showcase your skills. If you choose the placement year, you’ll gain real-world experience in the industry, giving you a head start for your career.

Focus Areas

“Programming, mathematics, core computer science systems, AI techniques including machine learning, symbolic and statistical AI, natural language processing, image and speech recognition, and real-world application through projects and industry placements.”

Learning Outcomes

“You’ll develop strong programming skills, understand data structures and algorithms, design and evaluate intelligent systems, work independently on a major project, and gain hands-on experience through placement and teamwork.”

Professional Alignment (Accreditation)

This course is accredited by the British Computer Society (BCS), meaning it meets professional standards and is recognised by employers in computing and AI.

Reputation (Employability Rankings)

  • The University of Huddersfield holds a Gold rating in the UK Teaching Excellence Framework (TEF 2023).

  • 84–95% of graduates from the School of Computing are in work or further study within 15 months of graduating.

  • The Uni Guide reports median graduate earnings of around £25.9k one year after graduation and £36.5k after five years.

Experiential Learning (Research, Projects, Internships etc.)

At Huddersfield, you won’t just be learning theory — you’ll be getting your hands dirty with real-world AI and computing projects right from the start. You’ll have access to specialist research centres, like the Centre for Autonomous and Intelligent Systems and the Centre for Sustainable Computing, which means your learning is informed by cutting-edge research and real industry challenges. Throughout the course, you’ll work on team projects, solve practical problems, and develop software and AI systems that you could actually use in the real world.

Your learning experience includes:

  • Hands-on coding and software tools: Practice programming, debugging, and visualising data with real software in modules like Introduction to Procedural Programming and Algorithms & Data Structures.

  • Team projects: Collaborate with classmates to design, build, and test prototypes in modules such as Project 1, developing teamwork, project planning, and problem-solving skills.

  • Industry placement opportunities: Take an optional placement year to gain real-world experience, applying your AI knowledge in a professional setting.

  • Research-informed labs: Work with AI techniques such as natural language processing, image and speech recognition, deep learning, and knowledge graphs in labs shaped by the university’s active research groups.

  • Access to specialised facilities: Use the university’s computing infrastructure, research centres, and industry-standard tools to bring your ideas to life.

Progression & Future Opportunities

 

Graduating from this course opens doors to exciting careers in computing and AI, whether you want to become a software engineer, a data analyst, a business intelligence developer, or a systems architect. You’ll leave Huddersfield ready to tackle real-world challenges in industries like finance, healthcare, robotics, and tech startups, with practical skills that employers are looking for. Here’s how the university helps you get there:

  • Career support: The University’s career services, including the Graduate Career Explorer, help you explore job options, write CVs, and prepare for interviews.

  • Employment success: Around 84–95% of graduates in computing and AI find work or continue their studies within 15 months.

  • Professional recognition: The degree is accredited by the British Computer Society (BCS), giving your CV extra weight with employers worldwide.

  • Industry-focused learning: Through practical projects, labs, and research-informed teaching, you gain skills in programming, AI techniques, and data analysis that directly match industry needs.

  • University–industry connections: Huddersfield works with real-world companies and uses job-market tools to ensure what you learn is relevant and up-to-date.

Further Academic Progression:
If you want to continue your studies, you could move on to a master’s degree in AI, data science, or software engineering, or even pursue doctoral research. The University offers postgraduate options that build directly on your undergraduate experience, giving you a path to specialise further or aim for advanced roles in tech and AI.

Program Key Stats

£17,600
£9,535
£ 29
Sept Intake : 14th Jan


73 %
Yes

Eligibility Criteria

CC*
3.0
16
65

NA
NA
6.0
87

Additional Information & Requirements

Career Options

  • Software Engineer
  • Data Analyst
  • Business Intelligence Developer
  • Systems Architect
  • Machine Learning Engineer
  • AI Specialist
  • Robotics Programmer
  • Data Scientist
  • Research Assistant in AI
  • Natural Language Processing (NLP) Developer
  • Computer Vision Engineer
  • Software Developer for Startups
  • IT Consultant
  • AI Product Manager
  • Cybersecurity Analyst

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