Tailoring your AI learning path

George Bargiannis

Subject Area Leader for Computing

Hi! I’m Dr George Bargiannis, Subject Area Leader for Computing and Information Systems and the Deputy Director of the Centre for Autonomous and Intelligent Systems at the University of Huddersfield.

What is Artificial Intelligence?  

Artificial Intelligence (AI) is an area of computer science that creates software and systems capable of performing tasks that usually rely on human intelligence. AI systems are designed to mimic or simulate human cognitive processes. Using intelligent algorithms, these systems can reason, learn, problem-solve, understand and make decisions. AI is used across a wide range of industries and sectors, changing daily lives and business operations in powerful ways, from fraud detection in the finance industry to precision farming in agriculture. 

Symbolic vs. Sub-Symbolic AI 

There are two major lines of research in AI, relying on: 

  • Symbolic representation of knowledge 

Symbolic AI is an approach to AI that uses formal logic and rule-based systems to solve structured problems. Knowledge is represented using symbols, and reasoning is performed by manipulating these symbols by predefined rules expressed in formal logic. 

  • Sub-symbolic representation based on data 

Sub-symbolic AI uses predominantly machine learning algorithms, such as ones based on neural networks, to find and learn patterns from data. Also referred to as statistical AI, this approach mimics how the brain processes information without relying on explicit rules or symbolic representations. 

There have been alternating cycles of one line dominating over the other throughout the history of AI. 

What are the strengths and weaknesses of symbolic and sub-symbolic AI? 

  Symbolic approaches Sub-symbolic approaches
Strengths

Limited data is enough 

 

Are easily explainable 

Get better with more data 

 

Can handle uncertainty 
Weaknesses

Get worse with more data 

 

Uncertainty may break them 

Require lots of data 

 

Not easily explainable (if at all) 

Symbolic and sub-symbolic AI approaches have many applications, each excelling in different scenarios, while there is also an increasing interest in hybrid approaches that combine elements of both.  

Why study Artificial Intelligence?  

There has been a major expansion in AI during the last ten years. The UK is striving to use intelligent technologies to position itself at the forefront of the digital revolution.  According to Forbes, the AI sector is now worth over  £16.8bn and employs more than 50,000 people – and the demand for AI talent is rapidly increasing in roles such as Data Analysts and Scientists, AI and Machine Learning Engineers and Big Data Specialists, as well as professionals whose role may oversee AI integration, such as digital marketing, business development and digital transformation.  

At Huddersfield, we offer a range of AI courses from undergraduate to postgraduate that will equip you with the skills needed to contribute to the growth of the AI sector in the UK and abroad. Our academics have world-leading expertise in research that applies AI methods to solve key societal challenges, meaning you'll develop knowledge and skills that are current and highly relevant to the industry.  

Postgraduate courses in AI at Huddersfield 

Artificial Intelligence MSc

This specialist course can be studied part-time online or full-time on campus and requires students to have a computer science undergraduate degree or professional qualification, or equivalent professional experience. This MSc aims to enhance your knowledge and skills to solve real-world problems using a range of AI technologies. A unique element of this course is that 50% of its content is sub-symbolic and 50% symbolic AI. You’ll cover approaches on the sub-symbolic side, including machine learning, data mining and robotics and you’ll also cover symbolic areas and applications such as knowledge representation and automated planning. This course is ideal if you wish to deepen your understanding of AI and progress your career where AI skills are in high demand. The course is also accredited by the British Computer Society (BCS), the Chartered Institute for the IT industry. Accreditation means you can be assured of the course’s quality, and it gives you a potential advantage when looking for a job. 

My time at the University of Huddersfield was instrumental in advancing my career. The course gave me the confidence and skills to address complex challenges in AI and software engineering. Although I was already in the industry, the new skills helped me adapt to emerging technologies and remain at the forefront of my field.

Marco Dinacci, Graduated from AI MSc in 2022, Technical Lead at Apple

Applied Artificial Intelligence MSc

This conversion course is open to graduates of any discipline. Like the Artificial Intelligence MSc, the course can be studied 100% online part-time or full-time on campus, so you can choose which study mode is best for you. Applied Artificial Intelligence MSc is ideal for those whose professional role involves managing data or AI projects and/or overseeing strategic change in organisations as they adopt AI, but who don’t have in-depth computer science knowledge. The course mostly covers sub-symbolic approaches such as machine learning and data mining, however, it also touches on aspects of symbolic AI in some modules. The Applied AI course is unique as it presents the opportunity to gain AI expertise alongside strategic management skills, and it’s accredited by the Chartered Management Institute (CMI) meaning you'll gain credits towards a CMI Level 7 Award in Strategic Management and Leadership Practice and be able to work towards Chartered Manager status (CMgr).  

Undergraduate courses in AI at Huddersfield 

Although all our undergraduate computer science degrees incorporate some aspects of artificial intelligence, two courses have a particular focus on AI.  

Computer Science with Artificial Intelligence BSc (Hons)

This course is ideal for those who haven’t yet completed an undergraduate degree, and who are looking to take their first steps towards a career in artificial intelligence or computer science more widely. You'll study a core computer science curriculum that provides a comprehensive understanding of the field, focusing on developing skills in programming and mathematics in your first year. Starting in your second year, you'll dive into specialised AI modules, exploring symbolic and sub-symbolic AI, along with their applications in areas like natural language processing, speech, and image recognition. In your third year, you also can gain industry experience through a placement. In your final year, you will delve deeper into AI approaches and applications, with two specialised modules, each focusing on advanced symbolic and advanced sub-symbolic topics. This course is accredited by BCS, which provides an indicator of quality to you and potential employers. It’s also accredited for Chartered IT Professional (CITP) status, BCS’s Chartered qualification. 

The AI modules were not only interesting, but also thoughtfully crafted to align with market needs, equipping me with skills and knowledge that are relevant to the field. The modules were regularly updated to reflect the latest trends for a subject that keeps evolving like AI. The unique teaching method made the learning process engaging and interactive by combining theoretical topics and hands-on practical work during sessions.

Mahmoud Fadlelmula, CS with AI BSc, AI Engineer (KTP Associate), Trio Media

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

Don’t have the traditional qualifications to study our BSc? This course is just like the Computer Science with Artificial Intelligence BSc (Hons) but is designed for those who have the capability to pursue a degree but do not have the pre-requisite qualifications to directly apply. The duration of the foundation element is one year, and, if you successfully pass, you’ll automatically progress on to the degree.

To summarise 

The UK AI sector is booming, with significant business activity and job opportunities paving the way for a rewarding career. The University of Huddersfield is striving to drive the sector forward by developing the next generation of AI professionals. Our courses are designed to offer something for everyone depending on your circumstances and career goals.  

To find out more about our AI courses, visit the links above. Please get in touch with study@hud.ac.uk if you have any further questions about the courses.