Data Science & Artificial Intelligence BSc

Data Science and Artificial Intelligence (AI) are two of the most exciting and fast-growing areas of modern technology. This combined degree explores how data is collected, processed and analysed, and how intelligent systems can use that data to make predictions, automate processes and solve real-world problems. A degree in Data Science & AI equips students with cutting-edge skills in programming, statistics, machine learning and advanced AI, making it an excellent choice for those who are curious, analytical and passionate about technology.

Course Structure

Most Data Science & AI degrees last three years full time, or four years with a placement year or study abroad. Some universities offer integrated master’s programmes (MSci/MEng) that extend to four or five years. Many are accredited by professional bodies such as BCS, The Chartered Institute for IT, or recognised by the National Cyber Security Centre (NCSC).

Teaching combines lectures, seminars, computer labs, group projects and applied industry challenges. Assessment usually includes coding assignments, data projects, presentations, exams and a final-year dissertation or applied AI project.

Typical Modules

Year 1 – Foundations of Data and AI

Introduction to Data Science

Programming Fundamentals (Python, R, C++ or Java)

Mathematics for Data Science and AI (Linear Algebra, Probability and Statistics)

Databases and Information Systems

Algorithms and Data Structures

Introduction to Artificial Intelligence

Year 2 – Core Development

Machine Learning and Data Mining

Neural Networks and Deep Learning

Natural Language Processing (NLP)

Big Data and Cloud Computing

Data Visualisation and Storytelling

Research Methods and Applied AI Projects

Year 3 – Advanced Applications

Reinforcement Learning and Advanced Machine Learning

Computer Vision and Image Recognition

Robotics and Intelligent Systems

AI Ethics, Law and Responsible Innovation

Advanced Data Analytics for Industry (finance, health, climate, etc.)

Final-Year Dissertation or Industry Project (often applying AI to real-world datasets)

Optional modules may include quantum computing, AI for healthcare, bioinformatics or cyber security.

Useful A-Level or BTEC Subjects

Entry requirements vary, but helpful subjects include:

• A levels: Mathematics is essential. Further Maths, Computer Science, and Physics are also excellent choices. Typical offers range from BBB–AAA.

  
  

• BTECs: Computing, IT or Engineering may be accepted, usually alongside A level Maths.

  
  

• International Baccalaureate: Higher Level Maths is strongly preferred, with Computer Science or Physics also useful.

  
  

• Strong numeracy and logical thinking are key to success in this course.

What Makes a Strong Application

Universities look for students who are analytical, innovative and enthusiastic about data-driven technologies. A strong application should include:

• Good academic results in maths, computing or science subjects.

  
  

• Evidence of coding or data projects, such as using AI libraries (TensorFlow, PyTorch) or entering data competitions (like Kaggle).

  
  

• A personal statement showing interest in data science, AI applications and their ethical implications.

  
  

• Extracurricular activities such as coding clubs, hackathons, robotics, or online courses in AI and machine learning.

Transferable Skills You Will Develop

Studying Data Science & AI develops both technical expertise and professional skills, including:

• Programming ability – coding in multiple languages (Python, R, Java, etc.).

  
  

• Mathematical and statistical analysis – applying algorithms to real-world data.

  
  

• Machine learning and AI knowledge – designing and training intelligent systems.

  
  

• Problem-solving – using data and AI to address complex challenges.

  
  

• Communication – presenting data insights clearly to non-technical audiences.

  
  

• Adaptability – keeping pace with fast-moving technological developments.

  
  

Wider Reading: Recommended Books for Aspiring Data Science & AI Students

Here are four accessible books to inspire and prepare you:

“The Signal and the Noise” by Nate Silver – A highly readable book on data predictions and uncertainty.

“Artificial Intelligence: A Guide for Thinking Humans” by Melanie Mitchell – A balanced and clear introduction to AI.

“Life 3.0: Being Human in the Age of Artificial Intelligence” by Max Tegmark – Explores how AI could shape the future of humanity.

“Naked Statistics” by Charles Wheelan – A fun and engaging introduction to statistical thinking.

Typical Pay After Graduation

Graduates in Data Science & AI are in high demand across industries. Entry-level roles such as junior data scientist, machine learning engineer or AI developer typically pay £30,000–£38,000. With experience, professionals in this field earn £45,000–£70,000, while senior AI engineers, research scientists or consultants can command £80,000–£120,000+, particularly in finance, healthcare and big tech.