Studying artificial intelligence abroad

What is artificial intelligence?

Artificial intelligence (AI) is the science and engineering of creating machines and software that can perform tasks which normally require human intelligence.

This includes recognising speech, understanding natural language, analysing images, solving problems, and making decisions.

AI can be found in areas like robotics, self-driving cars, medical diagnosis, financial forecasting and the development of large language models (LLMs) that can understand and generate human-like text.

The field combines knowledge from computer science, mathematics, engineering, and cognitive science.

As an AI student, you might explore how algorithms learn from data, how machines can recognise patterns, or how AI can adapt to new situations.

Your studies may involve coding in laboratories, running simulations, experimenting with neural networks, or working with real-world datasets, including those used to train and fine-tune LLMs, from industries around the globe.

Why study artificial intelligence abroad?

Learning AI in a different country exposes you to cutting-edge research, new technologies, and fresh perspectives. You might join a robotics lab in Japan, work with healthcare AI teams in Canada, or take part in a tech start-up project in Silicon Valley.

Studying abroad also provides opportunities to work with internationally recognised AI research groups developing LLMs and other advanced models.

By studying in different academic and cultural settings, you gain insight into how AI is being applied worldwide, from autonomous systems to natural language AI.

You also develop valuable global networks with researchers, innovators and industry leaders, which can help you collaborate on future projects or build an international career.

What you will study

AI degrees often combine theoretical foundations with practical applications. Common areas of study include:

• Machine Learning – teaching systems to improve their performance based on data.
• Computer Vision – enabling machines to interpret and process images and videos.
• Natural Language Processing – building systems that understand and generate human language, including advanced applications powered by LLMs.
• Robotics – designing and programming machines that can interact with the physical world.
• Neural Networks and Deep Learning – creating algorithms inspired by the human brain, which are central to the development of LLMs.
• AI Ethics and Policy – exploring the social, legal, and ethical impacts of AI technologies, including issues around bias, safety and accountability in LLMs.
• Data Science and Analytics – extracting insights from large, complex datasets.

Many programmes also offer internships with tech companies, industry collaborations, and opportunities to participate in research projects that tackle real-world challenges, such as training domain-specific LLMs for healthcare, law, or education.

Related subjects you might also like:

• Data Science
• Computer Science
• Robotics
• Cybersecurity
• Cognitive Science

Accreditation

At undergraduate level, students often graduate with a Bachelor of Science (BSc) in Artificial Intelligence or a related subject such as Computer Science with AI or Intelligent Systems. Some institutions also offer a Bachelor of Engineering (BEng) if the focus is on hardware and robotics.

At postgraduate level, options include a Master of Science (MSc) or Master of Research (MRes) in Artificial Intelligence, Machine Learning, or Data Science. Specialisations might cover areas like autonomous systems, AI in healthcare, human-computer interaction, or LLM development and deployment.

A PhD is usually required for careers in advanced AI research or academia.

In certain regions, professional certification is available for AI engineers and data scientists through recognised technology and computing bodies.

Careers

An AI degree can lead to careers in technology, research, industry, and beyond. Some graduates work as machine learning engineers, creating algorithms for applications like speech recognition, fraud detection, or LLM-powered chatbots.

Others become AI researchers, developing new techniques and pushing the boundaries of what AI can do.

You could also work in robotics, building autonomous vehicles or industrial automation systems. In business and finance, AI specialists analyse data to guide strategy and improve decision-making. Healthcare offers roles in developing AI tools for diagnosis, drug discovery and personalised medicine.

Some AI professionals move into roles in ethics, regulation, and policy, ensuring technology is used responsibly and benefits society as a whole.

Because AI skills are in high demand worldwide, graduates often find opportunities to work across countries, industries and disciplines, shaping the future of technology on a global scale.